Integrate DS4 execution parity in Rust

PLAN.md

@@ -45,18 +45,31 @@ execution targets one self-contained Mac.
 - Focused coverage exercises triggers, summary bounds and sanitizing, tail
   selection, queued guidance, checkpoint identity, running jobs, durable
   compaction markers, relaunch, and continued tool work after rebuild.
-- The next baseline gap is SSD streaming. Speculative decoding, steering, GLM
+- DeepSeek V4 Flash now supports DS4-compatible SSD expert streaming, legacy
-  5.2 execution, and DeepSeek V4 Pro execution are not implemented in the Rust
+  MTP, DSpark, and directional steering in the Rust executor. The optional
-  executor. Related catalog, validation, and preference plumbing must not be
+  modes are integrated into the same target-owned generation path used by
-  treated as runtime support.
+  local chat and the endpoint; disabling them preserves the resident greedy
+  token baseline. Runtime counters feed the Stats dashboard without inference
+  thread UI work.
+- Hardware-backed token oracles cover resident versus SSD execution, legacy
+  MTP, DSpark, SSD combined with both speculative modes, directional steering,
+  and target-only fallback. Differential endpoint scripts cover deterministic
+  output, finish state, and usage when reference and Rust servers are supplied.
+- GLM 5.2 has a dedicated Rust/Metal executor and DeepSeek V4 Pro uses the
+  generalized DeepSeek graph. Their remaining work is validation rather than
+  catalog plumbing: GLM MTP is still rejected, the full GLM/Pro hardware matrix
+  is incomplete, and Pro still needs explicit memory-admission verification.
+- The remaining model-independent execution gaps are fine-grained SSD cache
+  telemetry, the DS4 expert-locality profiler, and resident multi-session
+  server batching/scheduling.
 
 ## Delivery order
 
-1. **Next:** remaining DS4 execution technology, starting with SSD streaming, then
+1. **Next:** finish the remaining DS4 execution parity: detailed SSD cache
-   speculative decoding and the other Metal/runtime parity work.
+   telemetry, expert profiling, resident multi-session batching, GLM MTP, and
-2. Additional model execution: GLM 5.2 and DeepSeek V4 Pro.
+   the GLM/Pro hardware matrix.
-3. Product completion, exhaustive parity verification, and distribution.
+2. Product completion, exhaustive parity verification, and distribution.
-4. Optional extensions: Dev Brain and A2UI.
+3. Optional extensions: Dev Brain and A2UI.
 
 ## 1. Completed — tool hardening and safety
 
@@ -95,13 +108,21 @@ Exit criterion: use the agent for a real inspect/edit/test cycle while every
 side effect is visible, risky actions require consent, Stop works at every
 stage, and no file tool can escape the selected project.
 
-## 2. DS4 execution technology parity
+## 2. In progress — DS4 execution technology parity
 
 Goal: finish the model-independent Metal/runtime capabilities in `ds4.c`
 before adding larger model families. Every capability must be shared by local
 chat and the HTTP endpoint through the single process-wide model owner.
 
-### 2.1 SSD streaming — first runtime priority
+### 2.1 Implemented — SSD streaming
+
+Flash routed experts stream through the unchanged DS4 Metal kernels with
+automatic or explicit cache budgets, cold start, generated DS4 hotlists,
+preload controls, asynchronous I/O, and bounded cache eviction. Resident and
+SSD generation share token oracles. Engine atomics expose resident/cache bytes,
+requests, bytes read, and wait time; the UI samples and graphs their rates on
+its normal metrics thread. Native cache hit/miss, eviction, and preload-progress
+telemetry remains to be surfaced without changing the carried-over kernels.
 
 SSD streaming is the capacity prerequisite for larger models and therefore
 comes before GLM 5.2 and DeepSeek V4 Pro execution.
@@ -122,7 +143,14 @@ comes before GLM 5.2 and DeepSeek V4 Pro execution.
   the cache and I/O layer model-aware so later GLM/Pro milestones add policy and
   graph support rather than a second streaming subsystem.
 
-### 2.2 Speculative decoding: legacy MTP and DSpark
+### 2.2 Completed for Flash — legacy MTP and DSpark
+
+Both support GGUF formats are validated and executed by Rust. Draft generation,
+confidence/margin gates, target verification, accepted-prefix commit, rollback,
+strict/quality fallback, cancellation, checkpoint identity, streaming output,
+usage accounting, and Stats counters use the existing generation lifecycle.
+Sampled decoding remains target-only as in DS4. SSD streaming works with both
+modes, and long-chat DSpark prefill has a dedicated hardware regression.
 
 - Load and validate the optional Flash legacy-MTP or DSpark support GGUF without
   treating either as a standalone model. Preserve exact support-kind and target
@@ -142,7 +170,12 @@ comes before GLM 5.2 and DeepSeek V4 Pro execution.
 - GLM's in-model MTP path belongs to the GLM milestone, but it should reuse the
   verifier/session machinery established here.
 
-### 2.3 Remaining Metal execution controls
+### 2.3 Mostly completed — remaining Metal execution controls
+
+Directional steering, power throttling, prefill chunking, quality mode, weight
+warming, and simulated memory pressure now affect execution. CPU helper-thread
+and expert-profile settings are rejected instead of being persisted no-ops.
+Porting DS4's expert-locality profile output is the remaining item here.
 
 - Port directional steering files and exact FFN/attention application,
   including DS4 defaults, validation, zero-scale behavior, and checkpoint/model
@@ -154,7 +187,7 @@ comes before GLM 5.2 and DeepSeek V4 Pro execution.
 - Add hardware-backed token/activation fixtures for each mode and keep the
   ordinary resident Flash path unchanged when optional features are off.
 
-### 2.4 Single-machine server batching
+### 2.4 Remaining — single-machine server batching
 
 - Port DS4's resident multi-session batching and server scheduling only after
   the serialized path remains the correctness oracle. Preserve per-request
@@ -169,11 +202,12 @@ resident, SSD-streamed, MTP, DSpark, steering, and batched-server
 configurations, with optional modes off producing the same baseline behavior
 as today.
 
-## 3. Additional model execution
+## 3. Implemented executors — additional-model validation remains
 
-Start these only after the shared capacity and execution technology above is
+GLM 5.2 has a dedicated DSA/MLA executor and DeepSeek V4 Pro uses the generalized
-stable. Catalog entries, settings, tokenizer work, or GGUF validation alone do
+DeepSeek graph. Both are selectable runtimes, not catalog-only placeholders.
-not make a model selectable for inference.
+They are not complete parity milestones until the remaining items below pass on
+the installed hardware fixtures.
 
 ### GLM 5.2
 

scripts/execution_parity.py

@@ -0,0 +1,62 @@
+#!/usr/bin/env python3
+"""Run the DS4 token oracles, then the existing endpoint smoke corpus."""
+
+import argparse
+import pathlib
+import subprocess
+import sys
+
+
+ROOT = pathlib.Path(__file__).resolve().parent.parent
+HARDWARE_TESTS = (
+    "flash_resident_and_ssd_streaming_choose_the_same_tokens",
+    "legacy_mtp_runs_a_target_owned_greedy_cycle",
+    "dspark_runs_a_target_owned_greedy_cycle",
+    "ssd_streaming_supports_legacy_mtp_and_dspark",
+    "directional_steering_matches_the_ds4_token_oracle",
+)
+ENDPOINT_SCRIPTS = (
+    "endpoint_parity.py",
+    "endpoint_reasoning.py",
+    "endpoint_continuation.py",
+)
+
+
+def run(command):
+    print("+", " ".join(map(str, command)), flush=True)
+    subprocess.run(command, cwd=ROOT, check=True)
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--endpoint",
+        help="also run the existing endpoint parity scripts against this URL",
+    )
+    parser.add_argument(
+        "--skip-hardware",
+        action="store_true",
+        help="skip tests requiring the local Flash/MTP/DSpark GGUF fixtures",
+    )
+    args = parser.parse_args()
+
+    if not args.skip_hardware:
+        for test in HARDWARE_TESTS:
+            run(
+                [
+                    "cargo",
+                    "test",
+                    "--all-features",
+                    test,
+                    "--",
+                    "--ignored",
+                    "--nocapture",
+                ]
+            )
+    if args.endpoint:
+        for script in ENDPOINT_SCRIPTS:
+            run([sys.executable, ROOT / "scripts" / script, args.endpoint])
+
+
+if __name__ == "__main__":
+    main()

scripts/fixtures/mtp_copy_prompt.txt

@@ -0,0 +1,23 @@
+Reproduce the following C code EXACTLY, character for character, inside a single code block and output nothing else:
+
+```c
+static uint32_t clamp_u32(uint32_t v, uint32_t lo, uint32_t hi) {
+    if (v < lo) return lo;
+    if (v > hi) return hi;
+    return v;
+}
+
+static uint32_t ring_advance(uint32_t pos, uint32_t cap) {
+    uint32_t next = pos + 1u;
+    return next >= cap ? 0u : next;
+}
+
+static int scratch_init(scratch *s, uint32_t ctx_size) {
+    if (ctx_size == 0u) ctx_size = 1u;
+    s->ctx_size = ctx_size;
+    s->comp_cap = ctx_size / 4u + 2u;
+    s->rows = clamp_u32(s->comp_cap, 1u, 4096u);
+    s->head = 0u;
+    return s->rows > 0u ? 0 : -1;
+}
+```

scripts/speculative_parity.py

@@ -0,0 +1,131 @@
+#!/usr/bin/env python3
+"""Compare DS4 and Rust endpoints configured for the same decoding mode."""
+
+import argparse
+import json
+import urllib.request
+
+
+CASES = [
+    "hi",
+    "Reply with exactly three words describing a calm sea.",
+    "Write the first eight positive odd numbers separated by commas.",
+]
+
+
+def post(base_url, path, payload):
+    request = urllib.request.Request(
+        base_url.rstrip("/") + path,
+        data=json.dumps(payload).encode(),
+        headers={"Content-Type": "application/json"},
+    )
+    with urllib.request.urlopen(request, timeout=600) as response:
+        return json.load(response)
+
+
+def chat(base_url, prompt):
+    result = post(
+        base_url,
+        "/v1/chat/completions",
+        {
+            "model": "deepseek-v4-flash",
+            "messages": [{"role": "user", "content": prompt}],
+            "reasoning_effort": "none",
+            "temperature": 0,
+            "max_tokens": 64,
+        },
+    )
+    choice = result["choices"][0]
+    message = choice["message"]
+    return {
+        "content": message.get("content"),
+        "reasoning": message.get("reasoning_content"),
+        "finish_reason": choice.get("finish_reason"),
+        "usage": result.get("usage"),
+    }
+
+
+def anthropic(base_url, prompt):
+    result = post(
+        base_url,
+        "/v1/messages",
+        {
+            "model": "deepseek-v4-flash",
+            "messages": [{"role": "user", "content": prompt}],
+            "thinking": {"type": "disabled"},
+            "temperature": 0,
+            "max_tokens": 64,
+        },
+    )
+    return {
+        "content": result.get("content"),
+        "stop_reason": result.get("stop_reason"),
+        "usage": result.get("usage"),
+    }
+
+
+def responses(base_url, prompt):
+    result = post(
+        base_url,
+        "/v1/responses",
+        {
+            "model": "deepseek-v4-flash",
+            "input": prompt,
+            "reasoning": {"effort": "none"},
+            "temperature": 0,
+            "max_output_tokens": 64,
+        },
+    )
+    return {
+        "output": normalize(result.get("output")),
+        "status": result.get("status"),
+        "usage": result.get("usage"),
+    }
+
+
+def normalize(value):
+    if isinstance(value, list):
+        return [normalize(item) for item in value]
+    if isinstance(value, dict):
+        return {
+            key: normalize(item)
+            for key, item in value.items()
+            if key not in {"id", "created_at"}
+        }
+    return value
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("reference_url", help="DS4 reference server URL")
+    parser.add_argument("rust_url", help="Rust DS4Server URL in the same mode")
+    args = parser.parse_args()
+
+    failures = []
+    for prompt in CASES:
+        for name, request in (
+            ("chat", chat),
+            ("anthropic", anthropic),
+            ("responses", responses),
+        ):
+            reference = request(args.reference_url, prompt)
+            rust = request(args.rust_url, prompt)
+            if reference != rust:
+                failures.append(
+                    {
+                        "case": name,
+                        "prompt": prompt,
+                        "reference": reference,
+                        "rust": rust,
+                    }
+                )
+            else:
+                print(f"ok {name}: {prompt}")
+    if failures:
+        print(json.dumps(failures, indent=2, ensure_ascii=False))
+        raise SystemExit(1)
+    print("all deterministic DS4/Rust endpoint outputs and usage records match")
+
+
+if __name__ == "__main__":
+    main()

src/app.rs

@@ -90,6 +90,9 @@ pub(crate) struct App {
     pub(super) kv_cache_report: KvCacheReport,
     last_cache_scan: Instant,
     last_http_requests: u64,
+    last_ssd_selected_requests: u64,
+    last_ssd_requested_bytes: u64,
+    last_ssd_wait_ms: u64,
     #[cfg(target_os = "macos")]
     generation_service: Option<GenerationService>,
     #[cfg(target_os = "macos")]
@@ -136,6 +139,9 @@ pub(super) struct MetricsPoint {
     pub(super) http_requests_per_second: f32,
     pub(super) kv_read_bytes_per_second: f32,
     pub(super) kv_write_bytes_per_second: f32,
+    pub(super) ssd_requests_per_second: f32,
+    pub(super) ssd_bytes_per_second: f32,
+    pub(super) ssd_wait_ms_per_second: f32,
 }
 
 #[derive(Debug, Clone)]
@@ -154,6 +160,7 @@ pub(crate) enum Message {
     FocusNext,
     FocusPrevious,
     PreferenceModelChanged(ModelChoice),
+    PreferenceLegacyMtpChanged(bool),
     PreferenceDsparkChanged(bool),
     PreferenceTimeoutChanged(String),
     PreferenceEndpointPortChanged(String),
@@ -313,6 +320,9 @@ impl App {
                         kv_cache_report: KvCacheReport::default(),
                         last_cache_scan: Instant::now() - CACHE_SCAN_INTERVAL,
                         last_http_requests: 0,
+                        last_ssd_selected_requests: 0,
+                        last_ssd_requested_bytes: 0,
+                        last_ssd_wait_ms: 0,
                         #[cfg(target_os = "macos")]
                         generation_service,
                         #[cfg(target_os = "macos")]
@@ -416,6 +426,9 @@ impl App {
             kv_cache_report: KvCacheReport::default(),
             last_cache_scan: Instant::now() - CACHE_SCAN_INTERVAL,
             last_http_requests: 0,
+            last_ssd_selected_requests: 0,
+            last_ssd_requested_bytes: 0,
+            last_ssd_wait_ms: 0,
             #[cfg(target_os = "macos")]
             generation_service,
             #[cfg(target_os = "macos")]
@@ -535,6 +548,7 @@ impl App {
             Message::PreferenceModelChanged(model) => {
                 self.preference_draft.model = model;
                 if !model.supports_dspark() {
+                    self.preference_draft.legacy_mtp_enabled = false;
                     self.preference_draft.dspark_enabled = false;
                     self.preference_draft.dspark_confidence_threshold.clear();
                     self.preference_draft.dspark_strict = false;
@@ -552,6 +566,16 @@ impl App {
                 }
                 self.preference_error = None;
             }
+            Message::PreferenceLegacyMtpChanged(enabled) => {
+                self.preference_draft.legacy_mtp_enabled =
+                    self.preference_draft.model.supports_dspark() && enabled;
+                if self.preference_draft.legacy_mtp_enabled {
+                    self.preference_draft.dspark_enabled = false;
+                    self.preference_draft.dspark_confidence_threshold.clear();
+                    self.preference_draft.dspark_strict = false;
+                }
+                self.preference_error = None;
+            }
             Message::PreferenceDsparkChanged(enabled) => {
                 self.preference_draft.dspark_enabled =
                     self.preference_draft.model.supports_dspark() && enabled;
@@ -559,7 +583,7 @@ impl App {
                     self.preference_draft.dspark_confidence_threshold.clear();
                     self.preference_draft.dspark_strict = false;
                 } else {
-                    self.preference_draft.ssd_streaming = false;
+                    self.preference_draft.legacy_mtp_enabled = false;
                 }
                 self.preference_error = None;
             }
@@ -665,7 +689,7 @@ impl App {
                         .is_empty()
                 {
                     self.preference_draft.dspark_enabled = true;
-                    self.preference_draft.ssd_streaming = false;
+                    self.preference_draft.legacy_mtp_enabled = false;
                 }
                 self.preference_error = None;
             }
@@ -674,17 +698,12 @@ impl App {
                     self.preference_draft.model.supports_dspark() && value;
                 if self.preference_draft.dspark_strict {
                     self.preference_draft.dspark_enabled = true;
-                    self.preference_draft.ssd_streaming = false;
+                    self.preference_draft.legacy_mtp_enabled = false;
                 }
                 self.preference_error = None;
             }
             Message::PreferenceSsdChanged(value) => {
                 self.preference_draft.ssd_streaming = value;
-                if value {
-                    self.preference_draft.dspark_enabled = false;
-                    self.preference_draft.dspark_confidence_threshold.clear();
-                    self.preference_draft.dspark_strict = false;
-                }
                 self.preference_error = None;
             }
             Message::PreferenceSsdColdChanged(value) => {
@@ -1226,7 +1245,23 @@ impl App {
         let kv_read_bytes_per_second = kv_read_bytes as f32 / METRICS_SAMPLE_INTERVAL.as_secs_f32();
         let kv_write_bytes_per_second =
             kv_write_bytes as f32 / METRICS_SAMPLE_INTERVAL.as_secs_f32();
+        let sample_seconds = METRICS_SAMPLE_INTERVAL.as_secs_f32();
+        let ssd_requests_per_second = snapshot
+            .ssd_selected_requests
+            .saturating_sub(self.last_ssd_selected_requests)
+            as f32
+            / sample_seconds;
+        let ssd_bytes_per_second = snapshot
+            .ssd_requested_bytes
+            .saturating_sub(self.last_ssd_requested_bytes)
+            as f32
+            / sample_seconds;
+        let ssd_wait_ms_per_second =
+            snapshot.ssd_wait_ms.saturating_sub(self.last_ssd_wait_ms) as f32 / sample_seconds;
         self.last_http_requests = snapshot.http_requests;
+        self.last_ssd_selected_requests = snapshot.ssd_selected_requests;
+        self.last_ssd_requested_bytes = snapshot.ssd_requested_bytes;
+        self.last_ssd_wait_ms = snapshot.ssd_wait_ms;
         self.metrics_history.push_back(MetricsPoint {
             decode_tokens_per_second: if snapshot.phase == crate::metrics::RuntimePhase::Generating
             {
@@ -1238,6 +1273,9 @@ impl App {
             http_requests_per_second,
             kv_read_bytes_per_second,
             kv_write_bytes_per_second,
+            ssd_requests_per_second,
+            ssd_bytes_per_second,
+            ssd_wait_ms_per_second,
         });
         if self.metrics_history.len() > 120 {
             self.metrics_history.pop_front();

src/app/preferences.rs

@@ -3,6 +3,7 @@ use super::*;
 #[derive(Clone)]
 pub(super) struct PreferenceDraft {
     pub(super) model: ModelChoice,
+    pub(super) legacy_mtp_enabled: bool,
     pub(super) dspark_enabled: bool,
     pub(super) idle_timeout_minutes: String,
     pub(super) endpoint_port: String,
@@ -51,6 +52,7 @@ impl PreferenceDraft {
         let speculative = &runtime.speculative;
         Self {
             model: config.model,
+            legacy_mtp_enabled: speculative.legacy_mtp_enabled,
             dspark_enabled: speculative.dspark_enabled,
             idle_timeout_minutes: config.idle_timeout_minutes.to_string(),
             endpoint_port: config.endpoint.port.to_string(),
@@ -136,6 +138,7 @@ impl PreferenceDraft {
         Ok(SpeculativePreferences {
             mtp_draft_tokens: parse_positive_i32("MTP draft tokens", &self.mtp_draft_tokens)?,
             mtp_margin: parse_f32("MTP margin", &self.mtp_margin)?,
+            legacy_mtp_enabled: self.legacy_mtp_enabled,
             glm_mtp: self.glm_mtp,
             glm_mtp_timing: self.glm_mtp_timing,
             dspark_enabled: self.dspark_enabled,

src/app/view/preferences.rs

@@ -3,6 +3,19 @@ use iced::widget::column;
 
 impl App {
     pub(super) fn preferences_panel(&self) -> Element<'_, Message> {
+        let legacy_mtp_toggle: Option<fn(bool) -> Message> = self
+            .preference_draft
+            .model
+            .supports_dspark()
+            .then_some(Message::PreferenceLegacyMtpChanged);
+        let legacy_mtp = hint(
+            checkbox(
+                "Enable legacy MTP for this model",
+                self.preference_draft.legacy_mtp_enabled,
+            )
+            .on_toggle_maybe(legacy_mtp_toggle),
+            "Uses the managed one-stage MTP support GGUF. The target model verifies every drafted token; it is mutually exclusive with DSpark.",
+        );
         let dspark_toggle: Option<fn(bool) -> Message> = self
             .preference_draft
             .model
@@ -14,7 +27,7 @@ impl App {
                 self.preference_draft.dspark_enabled,
             )
             .on_toggle_maybe(dspark_toggle),
-            "Speculative decoding with the managed DSpark draft artifact: a small model proposes tokens that the main model verifies in one pass. Usually a large speedup, and it cannot be combined with SSD streaming.",
+            "Speculative decoding with the managed DSpark draft artifact: a small model proposes tokens that the main model verifies in one pass. Usually a large speedup; the target model may also stream routed experts from SSD.",
         );
         let glm_mtp_toggle: Option<fn(bool) -> Message> = (self.preference_draft.model
             == ModelChoice::Glm52)
@@ -311,6 +324,7 @@ impl App {
                     .on_toggle_maybe(glm_mtp_timing_toggle),
                     "Records per-stage timings of the speculative path to the log, to show where the acceleration actually goes. A diagnostic aid that costs a little throughput.",
                 ),
+                legacy_mtp,
                 dspark,
                 preference_input_row(
                     "DSpark confidence threshold",
@@ -326,7 +340,7 @@ impl App {
                     "Lets the draft model only propose, never decide: every token is sampled by the full model. Gives up some of the speedup in exchange for output identical to non-speculative decoding.",
                 ),
                 text(if self.preference_draft.model.supports_dspark() {
-                    "DSpark uses the managed support artifact; entering a threshold or enabling strict mode also enables DSpark."
+                    "Legacy MTP and DSpark use separate managed support artifacts; entering a DSpark threshold or enabling strict mode selects DSpark."
                 } else if self.preference_draft.model == ModelChoice::Glm52 {
                     "GLM MTP is integrated; DSpark is unavailable for this model."
                 } else {
@@ -339,9 +353,10 @@ impl App {
                     |engine| {
                         let settings = engine.speculative;
                         format!(
-                            "Engine: MTP draft {} • margin {} • GLM MTP {} • timing {} • DSpark {} • confidence {}{} • target-only {}",
+                            "Engine: MTP draft {} • margin {} • legacy MTP {} • GLM MTP {} • timing {} • DSpark {} • confidence {}{} • target-only {}",
                             settings.mtp_draft_tokens,
                             settings.mtp_margin,
+                            if self.preference_draft.legacy_mtp_enabled { "on" } else { "off" },
                             if settings.glm_mtp { "on" } else { "off" },
                             if settings.glm_mtp_timing { "on" } else { "off" },
                             if settings.dspark { "on" } else { "off" },
@@ -357,7 +372,7 @@ impl App {
                 hint(
                     checkbox("Enable SSD-backed model streaming", self.preference_draft.ssd_streaming)
                         .on_toggle(Message::PreferenceSsdChanged),
-                    "Leaves the routed expert weights on disk and pages them in as they are needed, so a model larger than this machine's memory still runs. Every cache miss waits for the SSD, and DSpark cannot run alongside it.",
+                    "Leaves the routed expert weights on disk and pages them in as they are needed, so a model larger than this machine's memory still runs. Every cache miss waits for the SSD; speculative support weights remain resident while target experts stream.",
                 ),
                 hint(
                     checkbox("Skip automatic expert preload", self.preference_draft.ssd_streaming_cold)
@@ -381,7 +396,7 @@ impl App {
                     text_input("Automatic", &self.preference_draft.ssd_preload_experts)
                         .on_input(Message::PreferenceSsdPreloadChanged),
                 ),
-                text("A blank full-layer value is automatic; an explicit 0 disables fully resident GLM layers. SSD streaming and DSpark are mutually exclusive.")
+                text("A blank full-layer value is automatic; an explicit 0 disables fully resident GLM layers. Flash legacy MTP and DSpark support weights remain resident when target experts stream.")
                     .size(12),
                 text(engine.as_ref().map_or_else(
                     || "Effective SSD settings will appear after valid values are entered."

src/app/view/stats.rs

@@ -198,6 +198,55 @@ impl App {
             .spacing(7)
             .into(),
         );
+        let ssd_activity = stats_panel(
+            "SSD STREAMING ACTIVITY · LAST 24 SECONDS",
+            column![
+                mini_chart(
+                    &self.metrics_history,
+                    |point| point.ssd_requests_per_second,
+                    Color::from_rgb8(240, 180, 70),
+                ),
+                row![
+                    text("Selected loads")
+                        .size(12)
+                        .color(Color::from_rgb8(240, 180, 70)),
+                    Space::with_width(Length::Fill),
+                    text(format!("{:.1}/s", latest.ssd_requests_per_second))
+                        .size(12)
+                        .color(muted_text()),
+                ],
+                mini_chart(
+                    &self.metrics_history,
+                    |point| point.ssd_bytes_per_second,
+                    Color::from_rgb8(67, 194, 203),
+                ),
+                row![
+                    text("Requested expert data")
+                        .size(12)
+                        .color(Color::from_rgb8(67, 194, 203)),
+                    Space::with_width(Length::Fill),
+                    text(format_rate(latest.ssd_bytes_per_second))
+                        .size(12)
+                        .color(muted_text()),
+                ],
+                mini_chart(
+                    &self.metrics_history,
+                    |point| point.ssd_wait_ms_per_second,
+                    Color::from_rgb8(220, 80, 86),
+                ),
+                row![
+                    text("Inference wait")
+                        .size(12)
+                        .color(Color::from_rgb8(220, 80, 86)),
+                    Space::with_width(Length::Fill),
+                    text(format!("{:.0} ms/s", latest.ssd_wait_ms_per_second))
+                        .size(12)
+                        .color(muted_text()),
+                ],
+            ]
+            .spacing(7)
+            .into(),
+        );
 
         let model = stats_panel(
             "MODEL CORE",
@@ -249,6 +298,86 @@ impl App {
             .spacing(9)
             .into(),
         );
+        let acceptance = if stats.drafted_tokens == 0 {
+            0.0
+        } else {
+            stats.accepted_draft_tokens as f64 / stats.drafted_tokens as f64
+        };
+        let target_passes = stats
+            .speculative_cycles
+            .saturating_add(stats.verifier_passes);
+        let effective_speedup = if target_passes == 0 {
+            1.0
+        } else {
+            stats
+                .speculative_cycles
+                .saturating_add(stats.accepted_draft_tokens) as f64
+                / target_passes as f64
+        };
+        let speculative = stats_panel(
+            "SPECULATIVE DECODING",
+            column![
+                metric_row(
+                    "Mode",
+                    match stats.speculative_mode {
+                        1 => "Legacy MTP",
+                        2 => "DSpark",
+                        _ => "Off",
+                    },
+                ),
+                metric_row("Cycles", format_count(stats.speculative_cycles)),
+                metric_row("Drafted", format_count(stats.drafted_tokens)),
+                metric_row("Accepted", format_count(stats.accepted_draft_tokens)),
+                metric_row("Acceptance", format!("{:.1}%", acceptance * 100.0)),
+                metric_row(
+                    "Target verifier passes",
+                    format_count(stats.verifier_passes)
+                ),
+                metric_row("Verifier wall time", format_milliseconds(stats.verifier_ms)),
+                metric_row(
+                    "Effective target-pass speedup",
+                    format!("{effective_speedup:.2}×")
+                ),
+            ]
+            .spacing(9)
+            .into(),
+        );
+        let ssd = stats_panel(
+            "SSD EXPERT STREAMING",
+            column![
+                metric_row("State", if stats.ssd_enabled { "Enabled" } else { "Off" }),
+                metric_row("Resident weights", format_bytes(stats.ssd_resident_bytes)),
+                metric_row("Expert cache", format_bytes(stats.ssd_cache_bytes)),
+                metric_row(
+                    "Cache capacity",
+                    format!("{} experts", stats.ssd_cache_experts)
+                ),
+                metric_row(
+                    "Preloaded",
+                    format!("{} experts", stats.ssd_preloaded_experts)
+                ),
+                metric_row(
+                    "Selected-load requests",
+                    format_count(stats.ssd_selected_requests)
+                ),
+                metric_row(
+                    "Requested expert bytes",
+                    format_bytes(stats.ssd_requested_bytes)
+                ),
+                metric_row("Selected-load wait", format_milliseconds(stats.ssd_wait_ms)),
+                metric_row(
+                    "Average load wait",
+                    format_milliseconds(
+                        stats
+                            .ssd_wait_ms
+                            .checked_div(stats.ssd_selected_requests)
+                            .unwrap_or(0)
+                    )
+                ),
+            ]
+            .spacing(9)
+            .into(),
+        );
         let cache = stats_panel(
             "KV CACHE",
             column![
@@ -352,10 +481,12 @@ impl App {
                     heading,
                     headline,
                     throughput,
+                    ssd_activity,
                     kv_io,
                     requests,
                     disc,
                     row![model, runtime].spacing(10),
+                    row![speculative, ssd].spacing(10),
                     row![cache, server].spacing(10),
                     text("Counters are published by the runtime with relaxed atomics and sampled by the UI every 200 ms.")
                         .size(11)

src/engine.rs

@@ -22,7 +22,22 @@ use std::sync::atomic::{AtomicBool, Ordering};
 #[cfg(target_os = "macos")]
 use std::time::Instant;
 use tokenizer::Tokenizer;
-use validation::{validate_dspark, validate_main};
+use validation::{SupportKind, validate_main, validate_support};
+
+#[cfg(target_os = "macos")]
+unsafe extern "C" {
+    fn mmap(
+        address: *mut std::ffi::c_void,
+        length: usize,
+        protection: i32,
+        flags: i32,
+        fd: i32,
+        offset: i64,
+    ) -> *mut std::ffi::c_void;
+    fn mlock(address: *const std::ffi::c_void, length: usize) -> i32;
+    fn munlock(address: *const std::ffi::c_void, length: usize) -> i32;
+    fn munmap(address: *mut std::ffi::c_void, length: usize) -> i32;
+}
 
 pub(crate) use validation::validate_model_artifact;
 
@@ -189,6 +204,7 @@ const GLM: Shape = Shape {
 pub(crate) struct Model {
     main: Gguf,
     support: Option<Gguf>,
+    support_kind: Option<SupportKind>,
     shape: Shape,
     tokenizer: Tokenizer,
 }
@@ -206,10 +222,17 @@ impl Model {
     #[allow(dead_code)]
     pub(crate) fn open(settings: &EngineSettings) -> Result<Self, String> {
         let mut model = Self::open_main(&settings.artifacts.model, settings.model)?;
+        if settings.execution.warm_weights {
+            model.main.warm()?;
+        }
         if let Some(path) = &settings.artifacts.mtp {
             let support = Gguf::open(path)?;
-            validate_dspark(&support, &model.shape)?;
+            let kind = validate_support(&support, &model.shape)?;
+            if settings.execution.warm_weights {
+                support.warm()?;
+            }
             model.support = Some(support);
+            model.support_kind = Some(kind);
         }
         Ok(model)
     }
@@ -228,6 +251,7 @@ impl Model {
         Ok(Self {
             main,
             support: None,
+            support_kind: None,
             shape,
             tokenizer,
         })
@@ -333,6 +357,7 @@ impl Model {
 #[cfg(target_os = "macos")]
 pub(crate) struct Generator {
     executor: metal::Executor,
+    _simulated_memory: Option<SimulatedMemory>,
     checkpoint: Option<PathBuf>,
     /// Token frontier of the last transient store, so continued checkpoints are
     /// spaced like ds4's `continued_last_store_tokens`.
@@ -340,6 +365,68 @@ pub(crate) struct Generator {
     metrics: Arc<Metrics>,
 }
 
+#[cfg(target_os = "macos")]
+struct SimulatedMemory {
+    address: std::ptr::NonNull<std::ffi::c_void>,
+    bytes: usize,
+}
+
+#[cfg(target_os = "macos")]
+impl SimulatedMemory {
+    fn acquire(bytes: u64) -> Result<Option<Self>, String> {
+        if bytes == 0 {
+            return Ok(None);
+        }
+        let bytes = usize::try_from(bytes).map_err(|_| "simulated memory size is too large")?;
+        let address = unsafe { mmap(std::ptr::null_mut(), bytes, 1 | 2, 2 | 0x1000, -1, 0) };
+        let Some(address) = std::ptr::NonNull::new(address) else {
+            return Err(format!(
+                "cannot reserve simulated used memory: {}",
+                std::io::Error::last_os_error()
+            ));
+        };
+        if address.as_ptr() as isize == -1 {
+            return Err(format!(
+                "cannot reserve simulated used memory: {}",
+                std::io::Error::last_os_error()
+            ));
+        }
+        let chunk = 256 * 1024 * 1024;
+        let mut locked = 0;
+        while locked < bytes {
+            let length = (bytes - locked).min(chunk);
+            let start = unsafe { address.as_ptr().cast::<u8>().add(locked) };
+            for page in (0..length).step_by(16 * 1024) {
+                unsafe { start.add(page).write((page / (16 * 1024)) as u8) };
+            }
+            unsafe { start.add(length - 1).write(1) };
+            if unsafe { mlock(start.cast(), length) } != 0 {
+                if locked != 0 {
+                    unsafe { munlock(address.as_ptr(), locked) };
+                }
+                unsafe { munmap(address.as_ptr(), bytes) };
+                return Err(format!(
+                    "cannot lock simulated used memory after {:.2} GiB: {}",
+                    locked as f64 / 1_073_741_824.0,
+                    std::io::Error::last_os_error()
+                ));
+            }
+            locked += length;
+        }
+        Ok(Some(Self { address, bytes }))
+    }
+}
+
+#[cfg(target_os = "macos")]
+impl Drop for SimulatedMemory {
+    fn drop(&mut self) {
+        unsafe {
+            munlock(self.address.as_ptr(), self.bytes);
+            munmap(self.address.as_ptr(), self.bytes);
+        }
+    }
+}
+
 #[derive(Clone)]
 pub(crate) struct ChatTurn {
     pub(crate) user: bool,
@@ -377,25 +464,41 @@ impl Generator {
                 "GLM MTP requires the shared speculative verifier, which is not enabled".into(),
             );
         }
-        if settings.speculative.dspark
+        let simulated_memory =
-            || (settings.ssd.enabled && settings.model != ModelChoice::Glm52)
+            SimulatedMemory::acquire(settings.diagnostics.simulated_used_memory_bytes)?;
-            || settings.steering.file.is_some()
-        {
-            return Err(
-                "DSpark, SSD streaming, and steering are not yet available in the Rust executor"
-                    .into(),
-            );
-        }
         let model = Model::open(settings)?;
         let executor = metal::Executor::open_configured(
             model,
             settings.context_tokens.max(1) as u32,
             settings.execution.quality,
             settings.execution.prefill_chunk,
+            settings.execution.power_percent,
+            settings.speculative,
             settings.ssd,
+            settings.steering.clone(),
         )?;
+        let stats = executor.execution_stats();
+        metrics.speculative_stats(
+            stats.speculative_mode,
+            stats.speculative_cycles,
+            stats.drafted_tokens,
+            stats.accepted_draft_tokens,
+            stats.verifier_passes,
+            stats.verifier_ms,
+        );
+        metrics.ssd_stats(
+            stats.ssd_enabled,
+            stats.ssd_resident_bytes,
+            stats.ssd_cache_bytes,
+            stats.ssd_cache_experts,
+            stats.ssd_preloaded_experts,
+            stats.ssd_selected_requests,
+            stats.ssd_requested_bytes,
+            stats.ssd_wait_ms,
+        );
         Ok(Self {
             executor,
+            _simulated_memory: simulated_memory,
             checkpoint: None,
             last_store_tokens: 0,
             metrics,
@@ -422,8 +525,9 @@ impl Generator {
             checkpoint,
             conversation_tag(&settings.system_prompt, settings.reasoning_mode, history),
         )?;
-        let (mut output, prompt_complete) =
+        let result = self.generate_inner(messages, settings, cancelled, &mut emit, &mut progress);
-            self.generate_inner(messages, settings, cancelled, &mut emit, &mut progress)?;
+        self.publish_execution_stats();
+        let (mut output, prompt_complete) = result?;
         let mut completed = messages.to_vec();
         completed.push(output.message.clone());
         output.previous_checkpoint_bytes =
@@ -442,6 +546,28 @@ impl Generator {
         Ok(output)
     }
 
+    fn publish_execution_stats(&self) {
+        let stats = self.executor.execution_stats();
+        self.metrics.speculative_stats(
+            stats.speculative_mode,
+            stats.speculative_cycles,
+            stats.drafted_tokens,
+            stats.accepted_draft_tokens,
+            stats.verifier_passes,
+            stats.verifier_ms,
+        );
+        self.metrics.ssd_stats(
+            stats.ssd_enabled,
+            stats.ssd_resident_bytes,
+            stats.ssd_cache_bytes,
+            stats.ssd_cache_experts,
+            stats.ssd_preloaded_experts,
+            stats.ssd_selected_requests,
+            stats.ssd_requested_bytes,
+            stats.ssd_wait_ms,
+        );
+    }
+
     pub(crate) fn generate_transient(
         &mut self,
         directory: &Path,
@@ -481,8 +607,9 @@ impl Generator {
             self.metrics.kv_lookup(KvLookup::MemoryHit);
         }
 
-        let (mut output, prompt_complete) =
+        let result = self.generate_inner(messages, settings, cancelled, &mut emit, &mut progress);
-            self.generate_inner(messages, settings, cancelled, &mut emit, &mut progress)?;
+        self.publish_execution_stats();
+        let (mut output, prompt_complete) = result?;
         let mut completed = messages.to_vec();
         completed.push(output.message.clone());
         output.previous_checkpoint_bytes = previous_checkpoint
@@ -809,6 +936,7 @@ impl Generator {
             }
             completed
         };
+        self.publish_execution_stats();
         if completed != suffix.len() {
             return Ok((
                 GenerationOutput {
@@ -826,11 +954,12 @@ impl Generator {
         progress(self.executor.position(), self.executor.context(), Some(0.0));
         let generation_started = Instant::now();
         let mut generated_tokens = 0_u32;
-        for _ in 0..settings
+        let generation_limit = settings
             .max_generated_tokens
             .max(0)
             .min((max_context - self.executor.position() as usize) as i32)
-        {
+            as u32;
+        while generated_tokens < generation_limit {
             if cancelled.load(Ordering::Relaxed) {
                 append_generated_bytes(&mut generated, reasoning, &mut pending_utf8, &[], true);
                 flush_generated(
@@ -887,6 +1016,46 @@ impl Generator {
                     true,
                 ));
             }
+            let cycle = if settings.temperature <= 0.0 {
+                self.executor.eval_speculative_greedy(
+                    token,
+                    generation_limit - generated_tokens,
+                    settings.reasoning_mode,
+                    cancelled,
+                )?
+            } else {
+                self.executor.eval(token)?;
+                vec![token]
+            };
+            self.publish_execution_stats();
+            for token in cycle {
+                if generated_tokens >= generation_limit
+                    || self
+                        .executor
+                        .model()
+                        .is_stop_token_for_reasoning(token, settings.reasoning_mode)
+                {
+                    append_generated_bytes(&mut generated, reasoning, &mut pending_utf8, &[], true);
+                    flush_generated(
+                        &mut generated,
+                        &mut emitted_reasoning,
+                        &mut emitted_content,
+                        &settings.stops,
+                        emit,
+                    );
+                    return Ok((
+                        GenerationOutput {
+                            message: generated,
+                            prompt_tokens: prompt_tokens as u32,
+                            cached_tokens: reused as u32,
+                            completion_tokens: generated_tokens,
+                            finish_reason: "stop",
+                            previous_checkpoint_bytes: None,
+                            checkpoint_bytes: 0,
+                        },
+                        true,
+                    ));
+                }
                 if self.executor.model().is_think_start_token(token) {
                     append_generated_bytes(&mut generated, reasoning, &mut pending_utf8, &[], true);
                     reasoning = true;
@@ -920,7 +1089,13 @@ impl Generator {
                     generated.reasoning_complete = true;
                     emit(false, String::new());
                 } else if let Some(bytes) = self.executor.model().token_bytes(token) {
-                append_generated_bytes(&mut generated, reasoning, &mut pending_utf8, &bytes, false);
+                    append_generated_bytes(
+                        &mut generated,
+                        reasoning,
+                        &mut pending_utf8,
+                        &bytes,
+                        false,
+                    );
                     let stopped = if reasoning {
                         let text = generated.reasoning.get_or_insert_default();
                         emit_safe_text(
@@ -957,7 +1132,6 @@ impl Generator {
                         ));
                     }
                 }
-            self.executor.eval(token)?;
                 generated_tokens += 1;
                 progress(
                     self.executor.position(),
@@ -968,6 +1142,7 @@ impl Generator {
                     ),
                 );
             }
+        }
         append_generated_bytes(&mut generated, reasoning, &mut pending_utf8, &[], true);
         flush_generated(
             &mut generated,

src/engine/gguf.rs

@@ -1,4 +1,4 @@
-use memmap2::{Mmap, MmapOptions};
+use memmap2::{Advice, Mmap, MmapOptions};
 use sha2::{Digest, Sha256};
 use std::collections::HashMap;
 use std::fs::File;
@@ -215,6 +215,23 @@ impl Gguf {
         self.max_tensor_bytes
     }
 
+    pub(super) fn warm(&self) -> Result<(), String> {
+        let start = self.data_offset as usize;
+        if start >= self.map.len() {
+            return Ok(());
+        }
+        self.map
+            .advise_range(Advice::WillNeed, start, self.map.len() - start)
+            .map_err(|error| format!("Cannot warm {}: {error}", self.path.display()))?;
+        let mut checksum = 0_u64;
+        for offset in (start..self.map.len()).step_by(16 * 1024) {
+            checksum = checksum.wrapping_add(u64::from(self.map[offset]));
+        }
+        checksum = checksum.wrapping_add(u64::from(self.map[self.map.len() - 1]));
+        std::hint::black_box(checksum);
+        Ok(())
+    }
+
     pub(super) fn tensor(&self, name: &str) -> Result<&Tensor, String> {
         self.tensors
             .get(name)
@@ -544,6 +561,7 @@ mod tests {
         assert_eq!(model.bytes("general.architecture").unwrap(), b"deepseek4");
         assert_eq!(model.tensor("weight").unwrap().dims, [1]);
         assert_eq!(model.tensor_data("weight").unwrap(), 1_f32.to_le_bytes());
+        model.warm().unwrap();
         fs::remove_file(path).unwrap();
     }
 

src/engine/metal/checkpoint.rs

@@ -301,6 +301,15 @@ impl DeepSeekExecutor {
         self.tokens = tokens;
         self.logits = logits;
         self.checkpoint_tag = checkpoint_tag;
+        if let Some(mtp) = &mut self.legacy_mtp {
+            mtp.draft_token = None;
+            mtp.raw_rows = 0;
+        }
+        if let Some(dspark) = &mut self.dspark {
+            dspark.capture_mask = 0;
+            dspark.cache_start = 0;
+            dspark.cache_len = 0;
+        }
         Ok(())
     }
 }

src/engine/metal/glm.rs

@@ -231,7 +231,7 @@ impl GlmExecutor {
         }
         let weights = GlmWeights::bind(&model)?;
         let admission = admission_bytes(&model, &weights, context, ssd)?;
-        let context_handle = Context::open(&model, quality, ssd.enabled, admission)?;
+        let context_handle = Context::open(&model, quality, ssd.enabled, admission, None)?;
         configure_streaming(&model, &weights, ssd)?;
         let scratch = GlmScratch::allocate(&model, context)?;
         let caches = (0..weights.layers.len())

src/engine/metal/gpu.rs

@@ -28,6 +28,14 @@ unsafe extern "C" {
         map_size: u64,
         max_tensor_bytes: u64,
     ) -> i32;
+    pub(super) fn ds4_gpu_set_model_map_spans(
+        model_map: *const c_void,
+        model_size: u64,
+        offsets: *const u64,
+        sizes: *const u64,
+        count: u32,
+        max_tensor_bytes: u64,
+    ) -> i32;
     pub(super) fn ds4_gpu_set_quality(quality: bool);
     pub(super) fn ds4_gpu_set_glm_model(enabled: bool);
     pub(super) fn ds4_gpu_set_ssd_streaming(enabled: bool);
@@ -39,6 +47,19 @@ unsafe extern "C" {
         gate_expert_bytes: u64,
         down_expert_bytes: u64,
     ) -> u32;
+    pub(super) fn ds4_gpu_stream_expert_cache_seed_experts(
+        table: *const StreamExpertTable,
+        expert_ids: *const i32,
+        expert_priorities: *const u32,
+        experts: u32,
+    ) -> i32;
+    pub(super) fn ds4_gpu_stream_expert_cache_begin_selected_load(
+        table: *const StreamExpertTable,
+        selected_ids: *const i32,
+        selected: u32,
+    ) -> i32;
+    pub(super) fn ds4_gpu_stream_expert_cache_note_service_thread();
+    pub(super) fn ds4_gpu_stream_expert_cache_reset_route_hotness();
     pub(super) fn ds4_gpu_glm_stream_expert_cache_begin_selected_load_tensor(
         table: *const StreamExpertTable,
         selected: *const GpuTensor,
@@ -79,8 +100,23 @@ unsafe extern "C" {
         src_offset: u64,
         count: u64,
     ) -> i32;
+    pub(super) fn ds4_gpu_pack_slot_rows_f32_tensor(
+        out: *mut GpuTensor,
+        slots: *const GpuTensor,
+        rows: u32,
+        width: u32,
+        slot_count: u32,
+        slot_stride: u32,
+    ) -> i32;
     pub(super) fn ds4_gpu_begin_commands() -> i32;
     pub(super) fn ds4_gpu_end_commands() -> i32;
+    pub(super) fn ds4_gpu_signal_selected_readback_ready(event: *mut u64) -> i32;
+    pub(super) fn ds4_gpu_wait_selected_readback_ready(
+        event: u64,
+        label: *const std::ffi::c_char,
+    ) -> i32;
+    pub(super) fn ds4_gpu_routed_moe_set_selected_override(selected: *const i32, count: u32)
+    -> i32;
 
     pub(super) fn ds4_gpu_embed_tokens_hc_tensor(
         out: *mut GpuTensor,
@@ -110,6 +146,13 @@ unsafe extern "C" {
         n: u32,
         eps: f32,
     ) -> i32;
+    pub(super) fn ds4_gpu_rms_norm_plain_rows_tensor(
+        out: *mut GpuTensor,
+        x: *const GpuTensor,
+        n: u32,
+        rows: u32,
+        eps: f32,
+    ) -> i32;
     pub(super) fn ds4_gpu_rms_norm_weight_tensor(
         out: *mut GpuTensor,
         x: *const GpuTensor,
@@ -119,6 +162,36 @@ unsafe extern "C" {
         n: u32,
         eps: f32,
     ) -> i32;
+    pub(super) fn ds4_gpu_rms_norm_weight_rows_tensor(
+        out: *mut GpuTensor,
+        x: *const GpuTensor,
+        map: *const c_void,
+        size: u64,
+        weight: u64,
+        n: u32,
+        rows: u32,
+        eps: f32,
+    ) -> i32;
+    pub(super) fn ds4_gpu_repeat_hc_tensor(
+        out: *mut GpuTensor,
+        x: *const GpuTensor,
+        embd: u32,
+        hc: u32,
+    ) -> i32;
+    pub(super) fn ds4_gpu_attention_noncausal_raw_batch_heads_tensor(
+        out: *mut GpuTensor,
+        map: *const c_void,
+        size: u64,
+        sinks: u64,
+        q: *const GpuTensor,
+        raw_cache: *const GpuTensor,
+        rows: u32,
+        visible_rows: u32,
+        cache_cap: u32,
+        raw_start: u32,
+        heads: u32,
+        head_dim: u32,
+    ) -> i32;
     pub(super) fn ds4_gpu_hc_rms_scale_project_f16_tensor(
         out: *mut GpuTensor,
         scale: *mut GpuTensor,
@@ -865,6 +938,14 @@ unsafe extern "C" {
         c: *const GpuTensor,
         count: u32,
     ) -> i32;
+    pub(super) fn ds4_gpu_directional_steering_project_tensor(
+        x: *mut GpuTensor,
+        directions: *const GpuTensor,
+        layer: u32,
+        width: u32,
+        rows: u32,
+        scale: f32,
+    ) -> i32;
     pub(super) fn ds4_gpu_add_rms_norm_weight_tensor(
         norm: *mut GpuTensor,
         sum: *mut GpuTensor,
@@ -1043,6 +1124,7 @@ impl Context {
         quality: bool,
         ssd_streaming: bool,
         admission_bytes: u64,
+        model_spans: Option<&[(u64, u64)]>,
     ) -> Result<Self, String> {
         check(unsafe { ds4_gpu_init() }, "Metal initialization")?;
         unsafe {
@@ -1059,7 +1141,19 @@ impl Context {
             ));
         }
         let data_offset = model.main.data_offset();
-        if let Err(error) = check(
+        let mapped = if let Some(spans) = model_spans {
+            let (offsets, sizes): (Vec<_>, Vec<_>) = spans.iter().copied().unzip();
+            unsafe {
+                ds4_gpu_set_model_map_spans(
+                    model.main.map_ptr().cast(),
+                    model.main.len(),
+                    offsets.as_ptr(),
+                    sizes.as_ptr(),
+                    spans.len() as u32,
+                    model.main.max_tensor_bytes(),
+                )
+            }
+        } else {
             unsafe {
                 ds4_gpu_set_model_map_range(
                     model.main.map_ptr().cast(),
@@ -1068,12 +1162,27 @@ impl Context {
                     model.main.len() - data_offset,
                     model.main.max_tensor_bytes(),
                 )
-            },
+            }
-            "model mapping",
+        };
-        ) {
+        if let Err(error) = check(mapped, "model mapping") {
             unsafe { ds4_gpu_cleanup() };
             return Err(error);
         }
+        if let Some(support) = &model.support {
+            let mapped = unsafe {
+                ds4_gpu_set_model_map_range(
+                    support.map_ptr().cast(),
+                    support.len(),
+                    support.data_offset(),
+                    support.len() - support.data_offset(),
+                    support.max_tensor_bytes(),
+                )
+            };
+            if let Err(error) = check(mapped, "support-model mapping") {
+                unsafe { ds4_gpu_cleanup() };
+                return Err(error);
+            }
+        }
         unsafe { ds4_gpu_set_quality(quality) };
         let model_file = File::open(model.main.path()).map_err(|error| {
             unsafe { ds4_gpu_cleanup() };
@@ -1209,6 +1318,20 @@ impl Buffer {
         )
     }
 
+    pub(super) fn write_f32(&self, values: &[f32]) -> Result<(), String> {
+        check(
+            unsafe {
+                ds4_gpu_tensor_write(
+                    self.raw(),
+                    0,
+                    values.as_ptr().cast(),
+                    std::mem::size_of_val(values) as u64,
+                )
+            },
+            "uploading floats",
+        )
+    }
+
     pub(super) fn fill(&self, value: f32, count: u64) -> Result<(), String> {
         call(
             unsafe { ds4_gpu_tensor_fill_f32(self.raw(), value, count) },

src/engine/validation.rs

@@ -7,7 +7,7 @@ pub(crate) fn validate_model_artifact(
 ) -> Result<(), String> {
     if support {
         let model = Gguf::open(path)?;
-        validate_dspark(&model, &FLASH)
+        validate_support(&model, &FLASH).map(|_| ())
     } else {
         let model = Model::open_main(path, expected)?;
         let summary = model.summary();
@@ -29,6 +29,192 @@ pub(crate) fn validate_model_artifact(
     }
 }
 
+#[derive(Clone, Copy, Debug, Eq, PartialEq)]
+pub(super) enum SupportKind {
+    LegacyMtp,
+    DSpark,
+}
+
+#[derive(Clone, Debug, Eq, PartialEq)]
+pub(super) struct DsparkConfig {
+    pub(super) block_size: u32,
+    pub(super) markov_rank: u32,
+    pub(super) noise_token: u32,
+    pub(super) target_layers: Vec<u32>,
+    pub(super) stages: u32,
+}
+
+pub(super) fn dspark_config(model: &Gguf) -> Result<DsparkConfig, String> {
+    let block_size = first_u32(
+        model,
+        &[
+            "deepseek4.dspark.block_size",
+            "deepseek4.dspark_block_size",
+            "dspark.block_size",
+        ],
+    )?;
+    let markov_rank = first_u32(
+        model,
+        &[
+            "deepseek4.dspark.markov_rank",
+            "deepseek4.dspark_markov_rank",
+            "dspark.markov_rank",
+        ],
+    )?;
+    let noise_token = first_u32(
+        model,
+        &[
+            "deepseek4.dspark.noise_token_id",
+            "deepseek4.dspark_noise_token_id",
+            "dspark.noise_token_id",
+        ],
+    )?;
+    let target_layers = first_u32s(
+        model,
+        &[
+            "deepseek4.dspark.target_layer_ids",
+            "deepseek4.dspark_target_layer_ids",
+            "dspark.target_layer_ids",
+        ],
+    )?;
+    let stages = model
+        .tensors
+        .keys()
+        .filter_map(|name| {
+            name.strip_prefix("mtp.")?
+                .split('.')
+                .next()?
+                .parse::<u32>()
+                .ok()
+        })
+        .max()
+        .map_or(0, |stage| stage + 1);
+    Ok(DsparkConfig {
+        block_size,
+        markov_rank,
+        noise_token,
+        target_layers: target_layers.to_vec(),
+        stages,
+    })
+}
+
+pub(super) fn validate_support(model: &Gguf, shape: &Shape) -> Result<SupportKind, String> {
+    if model.tensors.contains_key("mtp.0.e_proj.weight")
+        && model.tensors.contains_key("mtp.0.h_proj.weight")
+        && model.tensors.contains_key("mtp.0.hc_head_base.weight")
+    {
+        validate_legacy_mtp(model, shape)?;
+        Ok(SupportKind::LegacyMtp)
+    } else if model.metadata.contains_key("deepseek4.dspark.block_size")
+        || model.metadata.contains_key("deepseek4.dspark_block_size")
+        || model.metadata.contains_key("dspark.block_size")
+    {
+        validate_dspark(model, shape)?;
+        Ok(SupportKind::DSpark)
+    } else {
+        Err("support GGUF is neither legacy MTP nor DSpark".into())
+    }
+}
+
+fn validate_legacy_mtp(model: &Gguf, shape: &Shape) -> Result<(), String> {
+    if shape.model != ModelChoice::DeepSeekV4Flash {
+        return Err("legacy MTP support is available only for DeepSeek V4 Flash".into());
+    }
+    let prefix = "mtp.0";
+    let hc_dim = shape.embd * shape.hc;
+    let hc_mix = 2 * shape.hc + shape.hc * shape.hc;
+    let q_dim = shape.heads * shape.head_dim;
+    let output_low = shape.out_groups * shape.lora_o;
+    for (suffix, types, dims) in [
+        ("hc_head_base.weight", &[F32][..], vec![shape.hc]),
+        ("hc_head_fn.weight", PLAIN, vec![hc_dim, shape.hc]),
+        ("hc_head_scale.weight", &[F32][..], vec![1]),
+        ("e_proj.weight", &[Q8_0][..], vec![shape.embd, shape.embd]),
+        ("h_proj.weight", &[Q8_0][..], vec![shape.embd, shape.embd]),
+        ("enorm.weight", &[F32][..], vec![shape.embd]),
+        ("hnorm.weight", &[F32][..], vec![shape.embd]),
+        ("norm.weight", &[F32][..], vec![shape.embd]),
+        ("hc_attn_fn.weight", PLAIN, vec![hc_dim, hc_mix]),
+        ("hc_attn_scale.weight", &[F32][..], vec![3]),
+        ("hc_attn_base.weight", &[F32][..], vec![hc_mix]),
+        ("attn_norm.weight", &[F32][..], vec![shape.embd]),
+        (
+            "attn_q_a.weight",
+            &[Q8_0][..],
+            vec![shape.embd, shape.lora_q],
+        ),
+        ("attn_q_a_norm.weight", &[F32][..], vec![shape.lora_q]),
+        ("attn_q_b.weight", &[Q8_0][..], vec![shape.lora_q, q_dim]),
+        (
+            "attn_kv.weight",
+            &[Q8_0][..],
+            vec![shape.embd, shape.head_dim],
+        ),
+        ("attn_kv_a_norm.weight", &[F32][..], vec![shape.head_dim]),
+        ("attn_sinks.weight", &[F32][..], vec![shape.heads]),
+        (
+            "attn_output_a.weight",
+            &[Q8_0][..],
+            vec![
+                shape.head_dim * (shape.heads / shape.out_groups),
+                output_low,
+            ],
+        ),
+        (
+            "attn_output_b.weight",
+            &[Q8_0][..],
+            vec![output_low, shape.embd],
+        ),
+        ("hc_ffn_fn.weight", PLAIN, vec![hc_dim, hc_mix]),
+        ("hc_ffn_scale.weight", &[F32][..], vec![3]),
+        ("hc_ffn_base.weight", &[F32][..], vec![hc_mix]),
+        ("ffn_norm.weight", &[F32][..], vec![shape.embd]),
+        (
+            "ffn_gate_inp.weight",
+            PLAIN,
+            vec![shape.embd, shape.experts],
+        ),
+        ("exp_probs_b.bias", &[F32][..], vec![shape.experts]),
+        (
+            "ffn_gate_exps.weight",
+            ROUTED,
+            vec![shape.embd, shape.ff_expert, shape.experts],
+        ),
+        (
+            "ffn_up_exps.weight",
+            ROUTED,
+            vec![shape.embd, shape.ff_expert, shape.experts],
+        ),
+        (
+            "ffn_down_exps.weight",
+            ROUTED,
+            vec![shape.ff_expert, shape.embd, shape.experts],
+        ),
+        (
+            "ffn_gate_shexp.weight",
+            &[Q8_0][..],
+            vec![shape.embd, shape.ff_expert],
+        ),
+        (
+            "ffn_up_shexp.weight",
+            &[Q8_0][..],
+            vec![shape.embd, shape.ff_expert],
+        ),
+        (
+            "ffn_down_shexp.weight",
+            &[Q8_0][..],
+            vec![shape.ff_expert, shape.embd],
+        ),
+    ] {
+        expect(model, &format!("{prefix}.{suffix}"), types, &dims)?;
+    }
+    same_type(
+        model,
+        "mtp.0.ffn_gate_exps.weight",
+        "mtp.0.ffn_up_exps.weight",
+    )
+}
+
 pub(super) fn validate_main(model: &Gguf, expected: ModelChoice) -> Result<Shape, String> {
     let family = if model.bytes("general.architecture").ok() == Some(b"glm-dsa") {
         ModelFamily::Glm
@@ -575,38 +761,13 @@ pub(super) fn validate_dspark(model: &Gguf, shape: &Shape) -> Result<(), String>
     if shape.model != ModelChoice::DeepSeekV4Flash {
         return Err("DSpark support is available only for DeepSeek V4 Flash".into());
     }
-    let block_size = first_u32(
+    let DsparkConfig {
-        model,
+        block_size,
-        &[
+        markov_rank,
-            "deepseek4.dspark.block_size",
+        noise_token,
-            "deepseek4.dspark_block_size",
+        target_layers: targets,
-            "dspark.block_size",
+        stages,
-        ],
+    } = dspark_config(model)?;
-    )?;
-    let markov_rank = first_u32(
-        model,
-        &[
-            "deepseek4.dspark.markov_rank",
-            "deepseek4.dspark_markov_rank",
-            "dspark.markov_rank",
-        ],
-    )?;
-    let noise_token = first_u32(
-        model,
-        &[
-            "deepseek4.dspark.noise_token_id",
-            "deepseek4.dspark_noise_token_id",
-            "dspark.noise_token_id",
-        ],
-    )?;
-    let targets = first_u32s(
-        model,
-        &[
-            "deepseek4.dspark.target_layer_ids",
-            "deepseek4.dspark_target_layer_ids",
-            "dspark.target_layer_ids",
-        ],
-    )?;
     if !(1..=16).contains(&block_size) || markov_rank == 0 || noise_token >= shape.vocab as u32 {
         return Err("invalid DSpark block, Markov, or noise-token metadata".into());
     }
@@ -617,18 +778,6 @@ pub(super) fn validate_dspark(model: &Gguf, shape: &Shape) -> Result<(), String>
     {
         return Err("invalid DSpark target-layer metadata".into());
     }
-    let stages = model
-        .tensors
-        .keys()
-        .filter_map(|name| {
-            name.strip_prefix("mtp.")?
-                .split('.')
-                .next()?
-                .parse::<u32>()
-                .ok()
-        })
-        .max()
-        .map_or(0, |stage| stage + 1);
     if !(1..=8).contains(&stages) {
         return Err(format!("invalid DSpark stage count: {stages}"));
     }
@@ -1079,4 +1228,15 @@ mod tests {
             validate_model_artifact(path, ModelChoice::DeepSeekV4Flash, true).unwrap();
         }
     }
+
+    #[test]
+    fn installed_legacy_mtp_fixture_passes_the_target_layout() {
+        let path = Path::new("../ds4/gguf/DeepSeek-V4-Flash-MTP-Q4K-Q8_0-F32.gguf");
+        if path.exists() {
+            assert_eq!(
+                validate_support(&Gguf::open(path).unwrap(), &FLASH).unwrap(),
+                SupportKind::LegacyMtp
+            );
+        }
+    }
 }

src/metrics.rs

@@ -86,6 +86,20 @@ pub(crate) struct MetricsSnapshot {
     pub(crate) prompt_tokens: u64,
     pub(crate) cached_tokens: u64,
     pub(crate) completion_tokens: u64,
+    pub(crate) speculative_mode: u8,
+    pub(crate) speculative_cycles: u64,
+    pub(crate) drafted_tokens: u64,
+    pub(crate) accepted_draft_tokens: u64,
+    pub(crate) verifier_passes: u64,
+    pub(crate) verifier_ms: u64,
+    pub(crate) ssd_enabled: bool,
+    pub(crate) ssd_resident_bytes: u64,
+    pub(crate) ssd_cache_bytes: u64,
+    pub(crate) ssd_cache_experts: u64,
+    pub(crate) ssd_preloaded_experts: u64,
+    pub(crate) ssd_selected_requests: u64,
+    pub(crate) ssd_requested_bytes: u64,
+    pub(crate) ssd_wait_ms: u64,
     pub(crate) kv_lookups: u64,
     pub(crate) kv_hits: u64,
     pub(crate) kv_memory_hits: u64,
@@ -154,6 +168,20 @@ pub(crate) struct Metrics {
     prompt_tokens: AtomicU64,
     cached_tokens: AtomicU64,
     completion_tokens: AtomicU64,
+    speculative_mode: AtomicU8,
+    speculative_cycles: AtomicU64,
+    drafted_tokens: AtomicU64,
+    accepted_draft_tokens: AtomicU64,
+    verifier_passes: AtomicU64,
+    verifier_ms: AtomicU64,
+    ssd_enabled: AtomicBool,
+    ssd_resident_bytes: AtomicU64,
+    ssd_cache_bytes: AtomicU64,
+    ssd_cache_experts: AtomicU64,
+    ssd_preloaded_experts: AtomicU64,
+    ssd_selected_requests: AtomicU64,
+    ssd_requested_bytes: AtomicU64,
+    ssd_wait_ms: AtomicU64,
     kv_lookups: AtomicU64,
     kv_hits: AtomicU64,
     kv_memory_hits: AtomicU64,
@@ -227,6 +255,20 @@ impl Metrics {
             prompt_tokens: AtomicU64::new(0),
             cached_tokens: AtomicU64::new(0),
             completion_tokens: AtomicU64::new(0),
+            speculative_mode: AtomicU8::new(0),
+            speculative_cycles: AtomicU64::new(0),
+            drafted_tokens: AtomicU64::new(0),
+            accepted_draft_tokens: AtomicU64::new(0),
+            verifier_passes: AtomicU64::new(0),
+            verifier_ms: AtomicU64::new(0),
+            ssd_enabled: AtomicBool::new(false),
+            ssd_resident_bytes: AtomicU64::new(0),
+            ssd_cache_bytes: AtomicU64::new(0),
+            ssd_cache_experts: AtomicU64::new(0),
+            ssd_preloaded_experts: AtomicU64::new(0),
+            ssd_selected_requests: AtomicU64::new(0),
+            ssd_requested_bytes: AtomicU64::new(0),
+            ssd_wait_ms: AtomicU64::new(0),
             kv_lookups: AtomicU64::new(0),
             kv_hits: AtomicU64::new(0),
             kv_memory_hits: AtomicU64::new(0),
@@ -374,6 +416,52 @@ impl Metrics {
         self.source.store(WorkSource::None as u8, Ordering::Relaxed);
     }
 
+    pub(crate) fn speculative_stats(
+        &self,
+        mode: u8,
+        cycles: u64,
+        drafted: u64,
+        accepted: u64,
+        verifier_passes: u64,
+        verifier_ms: u64,
+    ) {
+        self.speculative_mode.store(mode, Ordering::Relaxed);
+        self.speculative_cycles.store(cycles, Ordering::Relaxed);
+        self.drafted_tokens.store(drafted, Ordering::Relaxed);
+        self.accepted_draft_tokens
+            .store(accepted, Ordering::Relaxed);
+        self.verifier_passes
+            .store(verifier_passes, Ordering::Relaxed);
+        self.verifier_ms.store(verifier_ms, Ordering::Relaxed);
+    }
+
+    #[allow(clippy::too_many_arguments)]
+    pub(crate) fn ssd_stats(
+        &self,
+        enabled: bool,
+        resident_bytes: u64,
+        cache_bytes: u64,
+        cache_experts: u64,
+        preloaded_experts: u64,
+        selected_requests: u64,
+        requested_bytes: u64,
+        wait_ms: u64,
+    ) {
+        self.ssd_enabled.store(enabled, Ordering::Relaxed);
+        self.ssd_resident_bytes
+            .store(resident_bytes, Ordering::Relaxed);
+        self.ssd_cache_bytes.store(cache_bytes, Ordering::Relaxed);
+        self.ssd_cache_experts
+            .store(cache_experts, Ordering::Relaxed);
+        self.ssd_preloaded_experts
+            .store(preloaded_experts, Ordering::Relaxed);
+        self.ssd_selected_requests
+            .store(selected_requests, Ordering::Relaxed);
+        self.ssd_requested_bytes
+            .store(requested_bytes, Ordering::Relaxed);
+        self.ssd_wait_ms.store(wait_ms, Ordering::Relaxed);
+    }
+
     pub(crate) fn unloaded(&self) {
         self.phase
             .store(RuntimePhase::Unloaded as u8, Ordering::Relaxed);
@@ -385,6 +473,8 @@ impl Metrics {
         self.decode_tps.store(0, Ordering::Relaxed);
         self.prefill_tps.store(0, Ordering::Relaxed);
         self.prefill_sample.store(0, Ordering::Relaxed);
+        self.speculative_stats(0, 0, 0, 0, 0, 0);
+        self.ssd_stats(false, 0, 0, 0, 0, 0, 0, 0);
         self.model_unloads.fetch_add(1, Ordering::Relaxed);
     }
 
@@ -534,6 +624,20 @@ impl Metrics {
             prompt_tokens: self.prompt_tokens.load(Ordering::Relaxed),
             cached_tokens: self.cached_tokens.load(Ordering::Relaxed),
             completion_tokens: self.completion_tokens.load(Ordering::Relaxed),
+            speculative_mode: self.speculative_mode.load(Ordering::Relaxed),
+            speculative_cycles: self.speculative_cycles.load(Ordering::Relaxed),
+            drafted_tokens: self.drafted_tokens.load(Ordering::Relaxed),
+            accepted_draft_tokens: self.accepted_draft_tokens.load(Ordering::Relaxed),
+            verifier_passes: self.verifier_passes.load(Ordering::Relaxed),
+            verifier_ms: self.verifier_ms.load(Ordering::Relaxed),
+            ssd_enabled: self.ssd_enabled.load(Ordering::Relaxed),
+            ssd_resident_bytes: self.ssd_resident_bytes.load(Ordering::Relaxed),
+            ssd_cache_bytes: self.ssd_cache_bytes.load(Ordering::Relaxed),
+            ssd_cache_experts: self.ssd_cache_experts.load(Ordering::Relaxed),
+            ssd_preloaded_experts: self.ssd_preloaded_experts.load(Ordering::Relaxed),
+            ssd_selected_requests: self.ssd_selected_requests.load(Ordering::Relaxed),
+            ssd_requested_bytes: self.ssd_requested_bytes.load(Ordering::Relaxed),
+            ssd_wait_ms: self.ssd_wait_ms.load(Ordering::Relaxed),
             kv_lookups: self.kv_lookups.load(Ordering::Relaxed),
             kv_hits: self.kv_hits.load(Ordering::Relaxed),
             kv_memory_hits: self.kv_memory_hits.load(Ordering::Relaxed),
@@ -866,6 +970,7 @@ mod tests {
         metrics.kv_write_finished(Duration::from_millis(20), false);
         assert_eq!(metrics.take_kv_io_sample(), (2_048, 4_096));
         assert_eq!(metrics.take_kv_io_sample(), (0, 0));
+        metrics.ssd_stats(true, 1_024, 2_048, 16, 4, 12, 8_192, 30);
         metrics.request_finished(
             WorkSource::LocalChat,
             Duration::from_millis(250),
@@ -890,6 +995,10 @@ mod tests {
         assert_eq!(snapshot.kv_prefix_hits, 1);
         assert_eq!(snapshot.kv_read_bytes, 2_048);
         assert_eq!(snapshot.kv_write_bytes, 4_096);
+        assert!(snapshot.ssd_enabled);
+        assert_eq!(snapshot.ssd_selected_requests, 12);
+        assert_eq!(snapshot.ssd_requested_bytes, 8_192);
+        assert_eq!(snapshot.ssd_wait_ms, 30);
         assert_eq!(snapshot.local_kv_bytes, 4_096);
         assert_eq!(snapshot.http_model_requests, 1);
     }

src/model.rs

@@ -14,8 +14,9 @@ pub(crate) const MODEL_CHOICES: [ModelChoice; 3] = [
     ModelChoice::DeepSeekV4Pro,
     ModelChoice::Glm52,
 ];
-pub(crate) const MANAGED_ARTIFACTS: [ManagedArtifactId; 4] = [
+pub(crate) const MANAGED_ARTIFACTS: [ManagedArtifactId; 5] = [
     ManagedArtifactId::DeepSeekV4Flash,
+    ManagedArtifactId::DeepSeekV4FlashMtp,
     ManagedArtifactId::DeepSeekV4FlashDspark,
     ManagedArtifactId::DeepSeekV4Pro,
     ManagedArtifactId::Glm52,
@@ -40,6 +41,14 @@ const FLASH_DSPARK: Artifact = Artifact {
     sha256: "8b3adf5942bec22ae2ea867cd7079cf13530ba83ffcffaf00f5de48664a1a34e",
     support: Some(true),
 };
+const FLASH_MTP: Artifact = Artifact {
+    label: "Legacy MTP support",
+    file_name: "DeepSeek-V4-Flash-MTP-Q4K-Q8_0-F32.gguf",
+    repository: DEEPSEEK_REPOSITORY,
+    size: 3_807_602_400,
+    sha256: "afd481ee689dce9037f70f39085fcdae5a5b096d521cdad43b19fa52bf8f4083",
+    support: Some(true),
+};
 const PRO: Artifact = Artifact {
     label: "DeepSeek V4 Pro model",
     file_name: "DeepSeek-V4-Pro-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-Instruct-imatrix.gguf",
@@ -94,9 +103,14 @@ impl ModelChoice {
     }
 
     #[cfg(test)]
-    fn artifacts(self, dspark_enabled: bool) -> impl Iterator<Item = &'static Artifact> {
+    fn artifacts(
+        self,
+        legacy_mtp_enabled: bool,
+        dspark_enabled: bool,
+    ) -> impl Iterator<Item = &'static Artifact> {
         [
             Some(self.main_artifact()),
+            (self.supports_dspark() && legacy_mtp_enabled).then_some(&FLASH_MTP),
             (self.supports_dspark() && dspark_enabled).then_some(&FLASH_DSPARK),
         ]
         .into_iter()
@@ -112,19 +126,26 @@ pub(crate) struct EngineArtifacts {
 
 pub(crate) fn engine_artifacts(
     model: ModelChoice,
+    legacy_mtp_enabled: bool,
     dspark_enabled: bool,
     models_path: &Path,
 ) -> EngineArtifacts {
     EngineArtifacts {
         model: model.main_artifact().path(model, models_path),
-        mtp: (model.supports_dspark() && dspark_enabled)
+        mtp: if model.supports_dspark() && legacy_mtp_enabled {
-            .then(|| FLASH_DSPARK.path(model, models_path)),
+            Some(FLASH_MTP.path(model, models_path))
+        } else if model.supports_dspark() && dspark_enabled {
+            Some(FLASH_DSPARK.path(model, models_path))
+        } else {
+            None
+        },
     }
 }
 
 #[derive(Clone, Copy, Debug, Eq, PartialEq)]
 pub(crate) enum ManagedArtifactId {
     DeepSeekV4Flash,
+    DeepSeekV4FlashMtp,
     DeepSeekV4FlashDspark,
     DeepSeekV4Pro,
     Glm52,
@@ -133,7 +154,9 @@ pub(crate) enum ManagedArtifactId {
 impl ManagedArtifactId {
     pub(crate) fn model(self) -> ModelChoice {
         match self {
-            Self::DeepSeekV4Flash | Self::DeepSeekV4FlashDspark => ModelChoice::DeepSeekV4Flash,
+            Self::DeepSeekV4Flash | Self::DeepSeekV4FlashMtp | Self::DeepSeekV4FlashDspark => {
+                ModelChoice::DeepSeekV4Flash
+            }
             Self::DeepSeekV4Pro => ModelChoice::DeepSeekV4Pro,
             Self::Glm52 => ModelChoice::Glm52,
         }
@@ -142,6 +165,7 @@ impl ManagedArtifactId {
     fn artifact(self) -> &'static Artifact {
         match self {
             Self::DeepSeekV4Flash => &FLASH,
+            Self::DeepSeekV4FlashMtp => &FLASH_MTP,
             Self::DeepSeekV4FlashDspark => &FLASH_DSPARK,
             Self::DeepSeekV4Pro => &PRO,
             Self::Glm52 => &GLM,

src/model/transfer.rs

@@ -331,15 +331,18 @@ mod tests {
             86_720_111_488
         );
         assert_eq!(ModelChoice::Glm52.main_artifact().size, 211_075_856_448);
-        assert_eq!(ModelChoice::DeepSeekV4Flash.artifacts(true).count(), 2);
+        assert_eq!(
-        assert_eq!(ModelChoice::Glm52.artifacts(true).count(), 1);
+            ModelChoice::DeepSeekV4Flash.artifacts(true, true).count(),
+            3
+        );
+        assert_eq!(ModelChoice::Glm52.artifacts(true, true).count(), 1);
 
         let id = SystemTime::now()
             .duration_since(UNIX_EPOCH)
             .unwrap()
             .as_nanos();
         let models_path = std::env::temp_dir().join(format!("ds4-server-models-{id}"));
-        let engine = engine_artifacts(ModelChoice::DeepSeekV4Flash, true, &models_path);
+        let engine = engine_artifacts(ModelChoice::DeepSeekV4Flash, false, true, &models_path);
         assert_eq!(
             engine.model.file_name(),
             Some(std::ffi::OsStr::new(FLASH.file_name))

src/settings.rs

@@ -23,6 +23,7 @@ const DEFAULT_KV_CONTINUED_INTERVAL_TOKENS: u32 = 10_000;
 pub(crate) struct SpeculativePreferences {
     pub(crate) mtp_draft_tokens: i32,
     pub(crate) mtp_margin: f32,
+    pub(crate) legacy_mtp_enabled: bool,
     pub(crate) glm_mtp: bool,
     pub(crate) glm_mtp_timing: bool,
     pub(crate) dspark_enabled: bool,
@@ -35,6 +36,7 @@ impl Default for SpeculativePreferences {
         Self {
             mtp_draft_tokens: 1,
             mtp_margin: 3.0,
+            legacy_mtp_enabled: false,
             glm_mtp: false,
             glm_mtp_timing: false,
             dspark_enabled: false,
@@ -59,6 +61,12 @@ impl SpeculativePreferences {
         if self.dspark_enabled && !model.supports_dspark() {
             return Err("DSpark is not available for the selected model.".into());
         }
+        if self.legacy_mtp_enabled && !model.supports_dspark() {
+            return Err("Legacy MTP is not available for the selected model.".into());
+        }
+        if self.legacy_mtp_enabled && self.dspark_enabled {
+            return Err("Legacy MTP and DSpark use different support artifacts.".into());
+        }
         if (self.dspark_confidence_threshold.is_some() || self.dspark_strict)
             && !self.dspark_enabled
         {
@@ -343,6 +351,9 @@ impl DiagnosticPreferences {
         if let Some(gib) = self.simulated_used_memory_gib {
             validate_gib("Simulated used memory", gib)?;
         }
+        if self.expert_profile_path.is_some() {
+            return Err("Expert profiling is not available in the Rust Metal executor yet.".into());
+        }
         Ok(())
     }
 
@@ -379,9 +390,6 @@ impl RuntimePreferences {
         self.steering.validate(model)?;
         self.diagnostics.validate()?;
         self.kv_cache.validate()?;
-        if self.ssd.enabled && self.speculative.dspark_enabled {
-            return Err("SSD streaming is not compatible with DSpark support.".into());
-        }
         Ok(())
     }
 
@@ -394,7 +402,12 @@ impl RuntimePreferences {
         self.validate(model)?;
         Ok(EngineSettings {
             model,
-            artifacts: model::engine_artifacts(model, self.speculative.dspark_enabled, models_path),
+            artifacts: model::engine_artifacts(
+                model,
+                self.speculative.legacy_mtp_enabled,
+                self.speculative.dspark_enabled,
+                models_path,
+            ),
             context_tokens,
             execution: self.execution.engine_settings(),
             speculative: self.speculative.engine_settings(),
@@ -438,6 +451,9 @@ impl ExecutionPreferences {
         {
             return Err("CPU helper threads is too large.".into());
         }
+        if self.cpu_threads.is_some() {
+            return Err("CPU helper threads do not apply to the Rust Metal executor.".into());
+        }
         if self
             .power_percent
             .is_some_and(|power| !(1..=100).contains(&power))
@@ -680,15 +696,23 @@ mod tests {
             (0, 0, 0)
         );
 
-        let tuned = ExecutionPreferences {
+        let unsupported_threads = ExecutionPreferences {
             cpu_threads: Some(100),
+            ..ExecutionPreferences::default()
+        };
+        assert!(
+            unsupported_threads
+                .validate(ModelChoice::DeepSeekV4Flash)
+                .is_err()
+        );
+
+        let tuned = ExecutionPreferences {
             power_percent: Some(50),
             prefill_chunk: Some(4096),
             ..ExecutionPreferences::default()
         };
         assert!(tuned.validate(ModelChoice::DeepSeekV4Flash).is_ok());
         assert!(tuned.validate(ModelChoice::Glm52).is_err());
-        assert_eq!(tuned.engine_settings().cpu_threads, MAX_CPU_THREADS);
     }
 
     #[test]
@@ -717,6 +741,21 @@ mod tests {
         };
         assert!(glm.validate(ModelChoice::Glm52).is_ok());
         assert!(glm.validate(ModelChoice::DeepSeekV4Pro).is_err());
+
+        let legacy = SpeculativePreferences {
+            legacy_mtp_enabled: true,
+            ..SpeculativePreferences::default()
+        };
+        assert!(legacy.validate(ModelChoice::DeepSeekV4Flash).is_ok());
+        assert!(legacy.validate(ModelChoice::DeepSeekV4Pro).is_err());
+        assert!(
+            SpeculativePreferences {
+                dspark_enabled: true,
+                ..legacy
+            }
+            .validate(ModelChoice::DeepSeekV4Flash)
+            .is_err()
+        );
     }
 
     #[test]
@@ -787,14 +826,14 @@ mod tests {
         assert_eq!(engine.steering.ffn_scale, 1.0);
         assert_eq!(engine.diagnostics.simulated_used_memory_bytes, 8 * GIB);
 
-        let incompatible = RuntimePreferences {
+        let combined = RuntimePreferences {
             speculative: SpeculativePreferences {
                 dspark_enabled: true,
                 ..SpeculativePreferences::default()
             },
             ..runtime
         };
-        assert!(incompatible.validate(ModelChoice::DeepSeekV4Flash).is_err());
+        assert!(combined.validate(ModelChoice::DeepSeekV4Flash).is_ok());
     }
 
     #[test]