Add native Qwen MTP speculation

assets/models/qwen38-flash-next-bare-speed-tensors.tsv

@@ -2492,15 +2492,15 @@ mtp.safetensors	mtp.layers.0.mlp.shared_expert.up_proj.weight	U32	640x320	4	64	a
 mtp.safetensors	mtp.layers.0.mlp.shared_expert_gate.biases	BF16	1x40	4	64	affine	140045196	140045276
 mtp.safetensors	mtp.layers.0.mlp.shared_expert_gate.scales	BF16	1x40	4	64	affine	140045276	140045356
 mtp.safetensors	mtp.layers.0.mlp.shared_expert_gate.weight	U32	1x320	4	64	affine	620915756	620917036
-mtp.safetensors	mtp.layers.0.mlp.switch_mlp.down_proj.biases	BF16	512x2560x20	2	64	affine	140966956	193395756
+mtp.safetensors	mtp.layers.0.mlp.switch_mlp.down_proj.biases	BF16	512x2560x20	4	32	affine	140966956	193395756
-mtp.safetensors	mtp.layers.0.mlp.switch_mlp.down_proj.scales	BF16	512x2560x20	2	64	affine	641468716	693897516
+mtp.safetensors	mtp.layers.0.mlp.switch_mlp.down_proj.scales	BF16	512x2560x20	4	32	affine	641468716	693897516
-mtp.safetensors	mtp.layers.0.mlp.switch_mlp.down_proj.weight	U32	512x2560x80	2	64	affine	1253145132	1672575532
+mtp.safetensors	mtp.layers.0.mlp.switch_mlp.down_proj.weight	U32	512x2560x80	4	32	affine	1253145132	1672575532
-mtp.safetensors	mtp.layers.0.mlp.switch_mlp.gate_proj.biases	BF16	512x640x80	2	64	affine	693897772	746326572
+mtp.safetensors	mtp.layers.0.mlp.switch_mlp.gate_proj.biases	BF16	512x640x80	4	32	affine	693897772	746326572
-mtp.safetensors	mtp.layers.0.mlp.switch_mlp.gate_proj.scales	BF16	512x640x80	2	64	affine	20277900	72706700
+mtp.safetensors	mtp.layers.0.mlp.switch_mlp.gate_proj.scales	BF16	512x640x80	4	32	affine	20277900	72706700
-mtp.safetensors	mtp.layers.0.mlp.switch_mlp.gate_proj.weight	U32	512x640x320	2	64	affine	760314412	1179744812
+mtp.safetensors	mtp.layers.0.mlp.switch_mlp.gate_proj.weight	U32	512x640x320	4	32	affine	760314412	1179744812
-mtp.safetensors	mtp.layers.0.mlp.switch_mlp.up_proj.biases	BF16	512x640x80	2	64	affine	87616396	140045196
+mtp.safetensors	mtp.layers.0.mlp.switch_mlp.up_proj.biases	BF16	512x640x80	4	32	affine	87616396	140045196
-mtp.safetensors	mtp.layers.0.mlp.switch_mlp.up_proj.scales	BF16	512x640x80	2	64	affine	1192852012	1245280812
+mtp.safetensors	mtp.layers.0.mlp.switch_mlp.up_proj.scales	BF16	512x640x80	4	32	affine	1192852012	1245280812
-mtp.safetensors	mtp.layers.0.mlp.switch_mlp.up_proj.weight	U32	512x640x320	2	64	affine	194808876	614239276
+mtp.safetensors	mtp.layers.0.mlp.switch_mlp.up_proj.weight	U32	512x640x320	4	32	affine	194808876	614239276
 mtp.safetensors	mtp.layers.0.mlp_hyper_connection.block_inject_weight.weight	BF16	4x10240				74345100	74427020
 mtp.safetensors	mtp.layers.0.mlp_hyper_connection.hc_norm.weight	BF16	10240				752921132	752941612
 mtp.safetensors	mtp.layers.0.mlp_hyper_connection.input_mix_weight_down.weight	BF16	320x10240				81062540	87616140

assets/models/qwen38-flash-next-bare-speed.json

@@ -11,7 +11,7 @@
     "converter": "qwen38-artifacts-v1-identity"
   },
   "tensor_inventory": "qwen38-flash-next-bare-speed-tensors.tsv",
-  "tensor_inventory_sha256": "369cdc7e53c09eaa5eff5cdcc49f0d0eab0ddc175f34965ba2ed1be2673d5858",
+  "tensor_inventory_sha256": "b5731e6febcf865d276a0e7b144da02375f2d7e3129594f271ee9c6c351f4c8f",
   "config": {
     "/architectures/0": "Qwen4ExpForConditionalGeneration",
     "/model_type": "qwen4_exp",
@@ -73,7 +73,7 @@
     {"class":"qsa","file":"model-00016-of-00017.safetensors","tensor":"language_model.model.layers.11.self_attn.indexer.index_qk_proj.weight","row":0,"values":64,"bits":8,"group_size":64,"sha256":"c803ea77148621a5d6dfa4060a52c75f57185234a0bec4771671f69336bb8346"},
     {"class":"gdn","file":"model-00016-of-00017.safetensors","tensor":"language_model.model.layers.0.linear_attn.A_log","row":0,"values":48,"sha256":"88c53a2a04bda1d96ee1ade6fa7dfa9c49d3245b1cc1e83673f02b7a36e07a85"},
     {"class":"ple","file":"ngram-table.safetensors","tensor":"ngram.weight","row":0,"values":64,"bits":4,"group_size":32,"sha256":"2243dd9766046bb80d98e3baf5e59ba246958cfe4f340ebce8c1fff57a2810d9"},
-    {"class":"mtp","file":"mtp.safetensors","tensor":"mtp.layers.0.mlp.switch_mlp.gate_proj.weight","row":0,"values":64,"bits":2,"group_size":64,"sha256":"6293cce5e1b25a4f35cb8af46e6e13b8378ec4ca84ec7f68859066dda48049cc"}
+    {"class":"mtp","file":"mtp.safetensors","tensor":"mtp.layers.0.mlp.switch_mlp.gate_proj.weight","row":0,"values":64,"bits":4,"group_size":32,"sha256":"393d82675ae7e25275243fd4907d3894146ac1c5662b601aae998c489d10af5c"}
   ],
   "files": [
     {"path":"model-00001-of-00017.safetensors","role":"core","size":4666167150,"sha256":"a27232c9434b9d8961f198cf36f44e228b3f23a5f8d874ba4ca8af32a1b23ffc"},

src/app/preferences.rs

@@ -865,16 +865,22 @@ impl App {
                 self.preference_error = None;
             }
             Message::PreferenceGlmMtpChanged(value) => {
-                self.preference_draft.glm_mtp =
+                self.preference_draft.glm_mtp = self
-                    self.preference_draft.acceleration_model.supports_glm_mtp() && value;
+                    .preference_draft
+                    .acceleration_model
+                    .supports_integrated_mtp()
+                    && value;
                 if !self.preference_draft.glm_mtp {
                     self.preference_draft.glm_mtp_timing = false;
                 }
                 self.preference_error = None;
             }
             Message::PreferenceGlmMtpTimingChanged(value) => {
-                self.preference_draft.glm_mtp_timing =
+                self.preference_draft.glm_mtp_timing = self
-                    self.preference_draft.acceleration_model.supports_glm_mtp() && value;
+                    .preference_draft
+                    .acceleration_model
+                    .supports_integrated_mtp()
+                    && value;
                 if self.preference_draft.glm_mtp_timing {
                     self.preference_draft.glm_mtp = true;
                 }

src/app/view/preferences.rs

@@ -17,12 +17,12 @@ impl App {
         let glm_mtp_toggle: Option<fn(bool) -> Message> = self
             .preference_draft
             .acceleration_model
-            .supports_glm_mtp()
+            .supports_integrated_mtp()
             .then_some(Message::PreferenceGlmMtpChanged);
         let glm_mtp_timing_toggle: Option<fn(bool) -> Message> = self
             .preference_draft
             .acceleration_model
-            .supports_glm_mtp()
+            .supports_integrated_mtp()
             .then_some(Message::PreferenceGlmMtpTimingChanged);
         let keep_vision_loaded_toggle: Option<fn(bool) -> Message> =
             (self.preference_draft.acceleration_model == ModelChoice::Glm53Flash)
@@ -608,13 +608,13 @@ impl App {
                 text("SPECULATIVE DECODING").size(11).color(muted_text()),
                 hint(
                     toggle(self.preference_draft.glm_mtp)
-                        .label("Enable integrated GLM MTP")
+                        .label("Enable integrated MTP")
                         .on_toggle_maybe(glm_mtp_toggle),
-                    "Uses the prediction head built into GLM for speculative decoding, so no separate draft model is loaded.",
+                    "Uses the selected model's managed prediction head for speculative decoding. Qwen loads its pinned MTP sidecar; GLM uses its embedded head.",
                 ),
                 hint(
                     toggle(self.preference_draft.glm_mtp_timing)
-                    .label("Log GLM MTP timing counters")
+                    .label("Log MTP timing counters")
                     .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.",
                 ),
@@ -644,8 +644,8 @@ impl App {
                 ),
                 text(if self.preference_draft.acceleration_model.supports_dspark() {
                     "DeepSeek V4 Flash 0731 uses its managed DSpark support artifact."
-                } else if self.preference_draft.acceleration_model.supports_glm_mtp() {
+                } else if self.preference_draft.acceleration_model.supports_integrated_mtp() {
-                    "GLM MTP is integrated; DSpark is unavailable for this model."
+                    "Integrated MTP is available; DSpark is unavailable for this model."
                 } else {
                     "No speculative-decoding support is available for this model."
                 })
@@ -656,7 +656,7 @@ impl App {
                     |engine| {
                         let settings = engine.speculative;
                         format!(
-                            "Engine: GLM MTP {} • timing {} • DSpark {} • confidence {}{} • target-only {} • exact sampling {}",
+                            "Engine: integrated MTP {} • timing {} • DSpark {} • confidence {}{} • target-only {} • exact sampling {}",
                             if settings.glm_mtp { "on" } else { "off" },
                             if settings.glm_mtp_timing { "on" } else { "off" },
                             if settings.dspark { "on" } else { "off" },

src/app/view/stats.rs

@@ -369,6 +369,7 @@ impl App {
                     match stats.speculative_mode {
                         2 => "DSpark",
                         3 => "GLM MTP",
+                        4 => "Qwen MTP",
                         _ => "Off",
                     },
                 ),
@@ -376,11 +377,27 @@ impl App {
                 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(
+                    "Mean accepted depth",
+                    if stats.speculative_cycles == 0 {
+                        "0.00".into()
+                    } else {
+                        format!(
+                            "{:.2}",
+                            stats.accepted_depth_total as f64 / stats.speculative_cycles as f64
+                        )
+                    }
+                ),
+                metric_row(
+                    "Maximum accepted depth",
+                    format_count(stats.accepted_depth_max)
+                ),
                 metric_row(
                     "Target verifier passes",
                     format_count(stats.verifier_passes)
                 ),
                 metric_row("Verifier wall time", format_milliseconds(stats.verifier_ms)),
+                metric_row("Repair wall time", format_milliseconds(stats.repair_ms)),
                 metric_row(
                     "Effective target-pass speedup",
                     format!("{effective_speedup:.2}×")

src/engine.rs

@@ -329,9 +329,13 @@ impl LoadedModel {
             )?;
             let context = u32::try_from(settings.context_tokens)
                 .map_err(|_| "Qwen context must be a positive whole number")?;
-            qwen::QwenModel::open(&settings.artifacts.model, context)
+            qwen::QwenModel::open_configured(
-                .map(Box::new)
+                &settings.artifacts.model,
-                .map(Self::Qwen)
+                context,
+                settings.speculative.glm_mtp,
+            )
+            .map(Box::new)
+            .map(Self::Qwen)
         } else {
             Model::open(settings).map(Box::new).map(Self::Gguf)
         }
@@ -815,8 +819,11 @@ impl Generator {
             stats.speculative_cycles,
             stats.drafted_tokens,
             stats.accepted_draft_tokens,
+            stats.accepted_depth_total,
+            stats.accepted_depth_max,
             stats.verifier_passes,
             stats.verifier_ms,
+            stats.repair_ms,
         );
         self.metrics.ssd_stats(SsdStats {
             enabled: stats.ssd_enabled,
@@ -1988,7 +1995,7 @@ fn sample_probabilities(
         .sum();
     let mut choice = rng.unit() * total;
     for (token, probability) in probabilities {
-        if Some(*token) == excluded {
+        if Some(*token) == excluded || !probability.is_finite() || *probability <= 0.0 {
             continue;
         }
         choice -= probability;
@@ -1999,7 +2006,9 @@ fn sample_probabilities(
     probabilities
         .iter()
         .rev()
-        .find(|(token, _)| Some(*token) != excluded)
+        .find(|(token, probability)| {
+            Some(*token) != excluded && probability.is_finite() && *probability > 0.0
+        })
         .map_or(0, |(token, _)| *token as i32)
 }
 
@@ -2028,6 +2037,67 @@ fn exact_delta_sample(
     )
 }
 
+#[cfg(any(target_os = "macos", test))]
+fn sample_from_logits(
+    logits: &[f32],
+    temperature: f32,
+    top_p: f32,
+    min_p: f32,
+    top_k: i32,
+    rng: &mut Rng,
+) -> i32 {
+    sample_probabilities(
+        &sampling_probabilities(logits, temperature, top_p, min_p, top_k),
+        rng,
+        None,
+    )
+}
+
+#[cfg(any(target_os = "macos", test))]
+#[allow(clippy::too_many_arguments)]
+fn exact_speculative_sample(
+    target_logits: &[f32],
+    draft_logits: &[f32],
+    draft: i32,
+    temperature: f32,
+    top_p: f32,
+    min_p: f32,
+    top_k: i32,
+    rng: &mut Rng,
+) -> (i32, bool) {
+    let mut target = sampling_probabilities(target_logits, temperature, top_p, min_p, top_k);
+    let mut proposal = sampling_probabilities(draft_logits, temperature, top_p, min_p, top_k);
+    target.sort_unstable_by_key(|(token, _)| *token);
+    proposal.sort_unstable_by_key(|(token, _)| *token);
+    let probability = |values: &[(usize, f32)], token: usize| {
+        values
+            .binary_search_by_key(&token, |(candidate, _)| *candidate)
+            .ok()
+            .map_or(0.0, |index| values[index].1)
+    };
+    let target_probability = probability(&target, draft as usize);
+    let draft_probability = probability(&proposal, draft as usize);
+    if draft_probability > 0.0 && rng.unit() <= (target_probability / draft_probability).min(1.0) {
+        return (draft, true);
+    }
+
+    let target_best = target
+        .iter()
+        .max_by(|left, right| left.1.total_cmp(&right.1))
+        .map_or(draft, |(token, _)| *token as i32);
+    let mut residual = Vec::with_capacity(target.len());
+    for (token, target_probability) in target {
+        let remaining = target_probability - probability(&proposal, token);
+        if remaining > 0.0 {
+            residual.push((token, remaining));
+        }
+    }
+    if residual.is_empty() {
+        return (target_best, false);
+    }
+    (sample_probabilities(&residual, rng, None), false)
+}
+
 #[cfg(any(target_os = "macos", test))]
 struct Rng(u64);
 
@@ -2113,6 +2183,34 @@ mod sampling_tests {
         assert_eq!((replacement, was_draft), (1, false));
     }
 
+    #[test]
+    fn probability_ratio_speculation_preserves_the_target_distribution() {
+        let target = [0.75_f32.ln(), 0.25_f32.ln()];
+        let proposal = [0.25_f32.ln(), 0.75_f32.ln()];
+        let mut rng = Rng::new(0x51a7_1c5e);
+        let mut counts = [0_u32; 2];
+        for _ in 0..40_000 {
+            let draft = sample_from_logits(&proposal, 1.0, 1.0, 0.0, 0, &mut rng);
+            let (token, _) =
+                exact_speculative_sample(&target, &proposal, draft, 1.0, 1.0, 0.0, 0, &mut rng);
+            counts[token as usize] += 1;
+        }
+        let observed = counts[0] as f32 / counts.iter().sum::<u32>() as f32;
+        assert!((observed - 0.75).abs() < 0.015, "observed {observed}");
+
+        let run = |seed| {
+            let mut rng = Rng::new(seed);
+            (0..32)
+                .map(|_| {
+                    let draft = sample_from_logits(&proposal, 1.0, 1.0, 0.0, 0, &mut rng);
+                    exact_speculative_sample(&target, &proposal, draft, 1.0, 1.0, 0.0, 0, &mut rng)
+                })
+                .collect::<Vec<_>>()
+        };
+        assert_eq!(run(77), run(77));
+        assert!(run(77).iter().any(|(_, accepted)| !accepted));
+    }
+
     #[test]
     fn sampling_probabilities_match_ds4_filter_order() {
         let probabilities = sampling_probabilities(&[0.0, 2.0, 1.0], 1.0, 0.8, 0.2, 0);

src/engine/metal.rs

@@ -14,7 +14,10 @@ use qwen::QwenExecutor;
 
 use super::gguf::{BF16, F16, F32, Gguf, IQ2_XXS, MXFP4, Q2_K, Q4_K, Q8_0, Tensor as GgufTensor};
 use super::validation::{DsparkConfig, SupportKind, dspark_config};
-use super::{LoadedModel, Model, ModelFamily, ModelRef, Rng, exact_delta_sample};
+use super::{
+    LoadedModel, Model, ModelFamily, ModelRef, Rng, exact_delta_sample, exact_speculative_sample,
+    sample_from_logits,
+};
 use crate::model::ModelChoice;
 use crate::settings::{
     EngineSpeculativeSettings, EngineSsdSettings, EngineSteeringSettings, ReasoningMode,
@@ -2949,8 +2952,11 @@ pub(super) struct ExecutionStats {
     pub(super) speculative_cycles: u64,
     pub(super) drafted_tokens: u64,
     pub(super) accepted_draft_tokens: u64,
+    pub(super) accepted_depth_total: u64,
+    pub(super) accepted_depth_max: u64,
     pub(super) verifier_passes: u64,
     pub(super) verifier_ms: u64,
+    pub(super) repair_ms: u64,
     pub(super) ssd_enabled: bool,
     pub(super) ssd_resident_bytes: u64,
     pub(super) ssd_cache_bytes: u64,
@@ -4460,9 +4466,11 @@ impl Executor {
                 .map(Self::Glm)
             }
             LoadedModel::Gguf(_) => unreachable!("Qwen never uses a GGUF model"),
-            LoadedModel::Qwen(model) => QwenExecutor::open(*model, context)
+            LoadedModel::Qwen(model) => {
-                .map(Box::new)
+                { QwenExecutor::open_configured(*model, context, speculative) }
-                .map(Self::Qwen),
+                    .map(Box::new)
+                    .map(Self::Qwen)
+            }
         }
     }
 
@@ -4495,10 +4503,17 @@ impl Executor {
                 executor.eval(token)?;
                 Ok(vec![token])
             }
-            Self::Qwen(executor) => {
+            Self::Qwen(executor) => executor.eval_speculative_sampled(
-                executor.eval(token)?;
+                token,
-                Ok(vec![token])
+                max_tokens,
-            }
+                reasoning,
+                temperature,
+                top_p,
+                min_p,
+                top_k,
+                rng,
+                cancelled,
+            ),
         }
     }
 
@@ -4548,9 +4563,7 @@ impl Executor {
                 executor.eval_speculative_greedy(token, max_tokens, cancelled)
             }
             Self::Qwen(executor) => {
-                let _ = (max_tokens, reasoning, cancelled);
+                executor.eval_speculative_greedy(token, max_tokens, reasoning, cancelled)
-                executor.eval(token)?;
-                Ok(vec![token])
             }
         }
     }

src/engine/qwen.rs

@@ -30,6 +30,8 @@ const MTP_TOKEN_RESERVE: u64 = 3;
 const GDN_STATE_BYTES: u64 = 113_246_208;
 const GDN_CONV_BYTES: u64 = 2_211_840;
 const PLE_CONV_BYTES: u64 = 184_320;
+const MTP_CAPTURE_HIDDEN_BYTES: u64 = 10_240 * 4;
+const MTP_CAPTURE_LOGITS_BYTES: u64 = 248_320 * 4;
 
 #[derive(Deserialize)]
 struct Manifest {
@@ -125,10 +127,22 @@ pub(super) struct QwenModel {
 }
 
 impl QwenModel {
+    #[cfg(test)]
     pub(super) fn open(root: &Path, context: u32) -> Result<Self, String> {
-        let loaded = load(root, context, false)?;
+        Self::open_configured(root, context, false)
+    }
+
+    pub(super) fn open_configured(
+        root: &Path,
+        context: u32,
+        enable_mtp: bool,
+    ) -> Result<Self, String> {
+        let loaded = load(root, context, enable_mtp)?;
         let mut bindings = loaded.bindings.core;
         bindings.extend(loaded.bindings.ple);
+        if enable_mtp {
+            bindings.extend(loaded.bindings.mtp);
+        }
         let mut paths = bindings
             .iter()
             .map(|binding| binding.file.clone())
@@ -176,7 +190,7 @@ impl QwenModel {
     pub(super) fn tensor(&self, name: &str) -> Result<&QwenTensor, String> {
         self.tensors
             .get(name)
-            .ok_or_else(|| format!("Qwen core tensor is missing: {name}"))
+            .ok_or_else(|| format!("Qwen tensor is missing: {name}"))
     }
 
     pub(super) fn map(&self, index: usize) -> (&[u8], &Path) {
@@ -424,10 +438,13 @@ fn validate_precision(name: &str, tensor: &ExpectedTensor) -> Result<(), String>
         (Some(bits @ (2 | 4 | 8)), Some(group @ (32 | 64)), Some("affine"))
             if tensor.dtype == "U32" || name.ends_with(".scales") || name.ends_with(".biases") =>
         {
-            if group == 32 && !name.starts_with("ngram.") {
+            if group == 32
+                && !name.starts_with("ngram.")
+                && !name.starts_with("mtp.layers.0.mlp.switch_mlp.")
+            {
                 return Err(format!("{name} unexpectedly uses 32-value groups"));
             }
-            if bits == 2 && !name.starts_with("mtp.") {
+            if bits == 2 {
                 return Err(format!("{name} unexpectedly uses 2-bit weights"));
             }
             Ok(())
@@ -666,7 +683,30 @@ pub(super) fn memory_plan(
         .and_then(|bytes| bytes.checked_add(QSA_FIXED_SCRATCH_BYTES))
         .and_then(|bytes| bytes.checked_add(topk_scratch))
         .ok_or_else(|| "Qwen prefill transient size overflows".to_owned())?;
-    let admitted_mtp = if enable_mtp { MTP_BYTES } else { 0 };
+    let admitted_mtp = if enable_mtp {
+        let capture_rows = MTP_TOKEN_RESERVE + 1;
+        let recurrent_capture = (GDN_STATE_BYTES
+            + GDN_CONV_BYTES
+            + PLE_CONV_BYTES
+            + MTP_CAPTURE_HIDDEN_BYTES
+            + MTP_CAPTURE_LOGITS_BYTES)
+            .checked_mul(capture_rows)
+            .ok_or_else(|| "Qwen MTP verifier capture size overflows".to_owned())?;
+        let mtp_attention = (KV_BYTES_PER_TOKEN + QSA_RAW_BYTES_PER_TOKEN)
+            .checked_mul(token_capacity)
+            .and_then(|bytes| {
+                QSA_POOLED_BYTES_PER_BLOCK
+                    .checked_mul(block_capacity)
+                    .and_then(|pooled| bytes.checked_add(pooled))
+            })
+            .ok_or_else(|| "Qwen MTP attention size overflows".to_owned())?;
+        MTP_BYTES
+            .checked_add(recurrent_capture)
+            .and_then(|bytes| bytes.checked_add(mtp_attention))
+            .ok_or_else(|| "Qwen MTP admission size overflows".to_owned())?
+    } else {
+        0
+    };
     let admission = CORE_BYTES
         .checked_add(admitted_mtp)
         .and_then(|bytes| bytes.checked_add(kv_and_recurrent))
@@ -706,7 +746,7 @@ mod tests {
         assert_eq!(plan.optional_mtp, MTP_BYTES);
         assert_eq!(plan.kv_and_recurrent, 7_564_812_288);
         assert_eq!(plan.prefill_transient, 28_056_068);
-        assert_eq!(plan.admission, 81_008_126_487);
+        assert_eq!(plan.admission, 88_924_002_839);
         let without_mtp = memory_plan(262_144, false, 512).unwrap();
         assert_eq!(without_mtp.optional_mtp, MTP_BYTES);
         assert_eq!(without_mtp.admission, 79_335_550_955);

src/metrics.rs

@@ -113,8 +113,11 @@ pub(crate) struct MetricsSnapshot {
     pub(crate) speculative_cycles: u64,
     pub(crate) drafted_tokens: u64,
     pub(crate) accepted_draft_tokens: u64,
+    pub(crate) accepted_depth_total: u64,
+    pub(crate) accepted_depth_max: u64,
     pub(crate) verifier_passes: u64,
     pub(crate) verifier_ms: u64,
+    pub(crate) repair_ms: u64,
     pub(crate) ssd_enabled: bool,
     pub(crate) ssd_resident_bytes: u64,
     pub(crate) ssd_cache_bytes: u64,
@@ -206,8 +209,11 @@ pub(crate) struct Metrics {
     speculative_cycles: AtomicU64,
     drafted_tokens: AtomicU64,
     accepted_draft_tokens: AtomicU64,
+    accepted_depth_total: AtomicU64,
+    accepted_depth_max: AtomicU64,
     verifier_passes: AtomicU64,
     verifier_ms: AtomicU64,
+    repair_ms: AtomicU64,
     ssd_enabled: AtomicBool,
     ssd_resident_bytes: AtomicU64,
     ssd_cache_bytes: AtomicU64,
@@ -304,8 +310,11 @@ impl Metrics {
             speculative_cycles: AtomicU64::new(0),
             drafted_tokens: AtomicU64::new(0),
             accepted_draft_tokens: AtomicU64::new(0),
+            accepted_depth_total: AtomicU64::new(0),
+            accepted_depth_max: AtomicU64::new(0),
             verifier_passes: AtomicU64::new(0),
             verifier_ms: AtomicU64::new(0),
+            repair_ms: AtomicU64::new(0),
             ssd_enabled: AtomicBool::new(false),
             ssd_resident_bytes: AtomicU64::new(0),
             ssd_cache_bytes: AtomicU64::new(0),
@@ -472,23 +481,32 @@ impl Metrics {
         self.source.store(WorkSource::None as u8, Ordering::Relaxed);
     }
 
+    #[allow(clippy::too_many_arguments)]
     pub(crate) fn speculative_stats(
         &self,
         mode: u8,
         cycles: u64,
         drafted: u64,
         accepted: u64,
+        accepted_depth_total: u64,
+        accepted_depth_max: u64,
         verifier_passes: u64,
         verifier_ms: u64,
+        repair_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.accepted_depth_total
+            .store(accepted_depth_total, Ordering::Relaxed);
+        self.accepted_depth_max
+            .store(accepted_depth_max, Ordering::Relaxed);
         self.verifier_passes
             .store(verifier_passes, Ordering::Relaxed);
         self.verifier_ms.store(verifier_ms, Ordering::Relaxed);
+        self.repair_ms.store(repair_ms, Ordering::Relaxed);
     }
 
     pub(crate) fn ssd_stats(&self, stats: SsdStats) {
@@ -540,7 +558,7 @@ 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.speculative_stats(0, 0, 0, 0, 0, 0, 0, 0, 0);
         self.ssd_stats(SsdStats::default());
         self.model_unloads.fetch_add(1, Ordering::Relaxed);
     }
@@ -695,8 +713,11 @@ impl Metrics {
             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),
+            accepted_depth_total: self.accepted_depth_total.load(Ordering::Relaxed),
+            accepted_depth_max: self.accepted_depth_max.load(Ordering::Relaxed),
             verifier_passes: self.verifier_passes.load(Ordering::Relaxed),
             verifier_ms: self.verifier_ms.load(Ordering::Relaxed),
+            repair_ms: self.repair_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),

src/model.rs

@@ -128,8 +128,8 @@ impl ModelChoice {
         self == Self::Qwen38FlashNext
     }
 
-    pub(crate) fn supports_glm_mtp(self) -> bool {
+    pub(crate) fn supports_integrated_mtp(self) -> bool {
-        self.is_glm()
+        self.is_glm() || self.is_qwen38()
     }
 
     pub(crate) fn main_artifact_size(self) -> u64 {

src/model/qwen.rs

@@ -13,7 +13,7 @@ use std::sync::atomic::{AtomicBool, AtomicU64, Ordering};
 pub(super) const LABEL: &str = "Qwen3.8 Flash Next Bare Speed artifact set";
 pub(super) const REPOSITORY: &str = "Youssofal/Qwen3.8-Flash-Next-MTPLX-Bare-Speed";
 pub(super) const REVISION: &str = "74559cdf34fbfc0b593de72d17e93f37fd4f9ea7";
-const MANIFEST_SHA256: &str = "eeec490fd3d0c0b1c9093be0a7fe7b9be4b49389ed5276de7530c2d3c11290ca";
+const MANIFEST_SHA256: &str = "6f1172de47fa30b9602e13fc7ad14e578a813bb5b1fab8f0ef320041aac6c19a";
 const MANIFEST_BYTES: &[u8] =
     include_bytes!("../../assets/models/qwen38-flash-next-bare-speed.json");
 

src/settings.rs

@@ -45,10 +45,10 @@ pub(crate) struct SpeculativePreferences {
 impl SpeculativePreferences {
     pub(crate) fn validate(&self, model: ModelChoice) -> Result<(), String> {
         if self.glm_mtp_timing && !self.glm_mtp {
-            return Err("GLM MTP timing requires GLM MTP.".into());
+            return Err("MTP timing requires integrated MTP.".into());
         }
-        if !model.supports_glm_mtp() && (self.glm_mtp || self.glm_mtp_timing) {
+        if !model.supports_integrated_mtp() && (self.glm_mtp || self.glm_mtp_timing) {
-            return Err("GLM MTP is available only for GLM models.".into());
+            return Err("Integrated MTP is unavailable for the selected model.".into());
         }
         if self.keep_vision_loaded && model != ModelChoice::Glm53Flash {
             return Err("Persistent vision weights are available only for GLM 5.3 Flash.".into());
@@ -83,7 +83,7 @@ impl SpeculativePreferences {
     }
 }
 
-#[derive(Clone, Copy, Debug, PartialEq)]
+#[derive(Clone, Copy, Debug, Default, PartialEq)]
 pub(crate) struct EngineSpeculativeSettings {
     pub(crate) glm_mtp: bool,
     pub(crate) glm_mtp_timing: bool,

tools/qwen38-artifacts.rs

@@ -657,7 +657,7 @@ fn precision_assignments(
     reject_unassigned_quantized(&core, &assignments)?;
 
     let mtp = tensor_headers(manifest, source, Some("mtp"), complete)?;
-    add_inferred_sidecar(&mtp, 64, &mut assignments)?;
+    add_inferred_sidecar(&mtp, &mut assignments)?;
     let ple = tensor_headers(manifest, source, Some("ple"), complete)?;
     let ple_group = config
         .pointer("/mtplx_recipe/ngram/group_size")
@@ -711,7 +711,6 @@ fn validate_unquantized(base: &str, tensors: &BTreeMap<String, Tensor>) -> Resul
 
 fn add_inferred_sidecar(
     tensors: &BTreeMap<String, Tensor>,
-    group_size: u64,
     assignments: &mut BTreeMap<String, Quantization>,
 ) -> Result<(), String> {
     for (name, tensor) in tensors {
@@ -732,6 +731,11 @@ fn add_inferred_sidecar(
             .shape
             .last()
             .ok_or_else(|| format!("{base}.scales has no dimensions"))?;
+        let group_size = if base.contains(".switch_mlp.") {
+            32
+        } else {
+            64
+        };
         let pack = groups
             .checked_mul(group_size)
             .and_then(|columns| columns.checked_div(packed))