[Cookbook] Kimi-K3: add measured B300 1x8 Unified 8k/1k speed numbers (#37878)

Co-authored-by: Claude Opus 5 <noreply@anthropic.com>

docs/cookbook/autoregressive/Moonshotai/Kimi-K3.mdx

@@ -81,6 +81,16 @@ import { KimiK3MambaRatioCalculator } from "/src/snippets/_kimi_k3_mamba_ratio_c
 
 <Deployment config={config} benchmarks={benchmarks} />
 
+<Note>
+  B300 1×8 Unified speed numbers are measured on `v0.5.18 @ 71de97b2` with `--random-range-ratio 1.0`,
+  `--warmup-requests 64`, `--flush-cache`, at ISL 8192 / OSL 1024. DSPARK cells pin the acceptance
+  length via the serve env `SGLANG_SIMULATE_ACC_LEN=4.5` — they report what block size 7 delivers at
+  that acceptance, not a measured acceptance rate for this workload. Balanced DSPARK adds
+  `--max-running-requests 256`; without it speculation resets the cap to 48. The KDA state pool still
+  clamps admission below that (101 / 68 / 91 / 60 concurrent requests for MXFP4 NOSPEC / MXFP4 DSPARK /
+  NVFP4 NOSPEC / NVFP4 DSPARK), which is why no point past concurrency 64 is published for Balanced.
+</Note>
+
 ### Mamba ratio calculator
 
 <KimiK3MambaRatioCalculator />
@@ -124,9 +134,10 @@ are scheduled to release by July 27, 2026**. The recipes on this page were valid
 repository (`moonshotai/Kimi-K3`) and a public `lmsysorg/sglang` image with K3 support will be
 available at launch.
 
-Every cell in the Deploy panel above is currently marked **Final Verification In Progress**: the
+The B300 1×8 `Unified` Low-Latency and Balanced cells are **Verified** — a speed round on the final
-recipe runs, but its serving round on the final weights and current code is still open. Re-measure
+weights is published below. Every other cell is still marked **Final Verification In Progress**: the
-throughput and accuracy before you rely on any of them.
+recipe runs, but its serving round on the final weights and current code is still open. Accuracy has
+not been re-measured on any cell — re-measure before you rely on one.
 </Note>
 
 **Recommended generation:** `temperature=1.0`, `top_p=0.95`, `presence_penalty=0`, `frequency_penalty=0` (fixed by the model; informational — do not hardcode in sample code).
@@ -155,7 +166,7 @@ Speculation: DSPARK holds block size + 1 (= 8) intermediate states per request
 
 **Context length.** `--context-length` bounds the longest accepted request plus some context-scaled buffers; it does not size the KV pool. For long context the lever that adds capacity is `fp8_e4m3` KV.
 
-**DSPARK.** Adds `--speculative-algorithm DSPARK` plus the draft checkpoint on top of the showing strategy. Leave `--speculative-draft-attention-backend` unset. No serving round on the final draft checkpoint has landed — measure against the same recipe running NOSPEC before adopting.
+**DSPARK.** Adds `--speculative-algorithm DSPARK` plus the draft checkpoint on top of the showing strategy. Leave `--speculative-draft-attention-backend` unset. The published B300 DSPARK numbers pin the acceptance length with `SGLANG_SIMULATE_ACC_LEN`, so no measured acceptance rate exists for a real workload yet — measure against the same recipe running NOSPEC before adopting.
 
 **Per-platform notes:**
 
@@ -179,7 +190,7 @@ Speculation: DSPARK holds block size + 1 (= 8) intermediate states per request
 - Calculator ratios run well above 1 here (`r > 1` is legal): `bfloat16` state buys admission, `fp8` KV buys context.
 - Don't use EP with an a2a backend: a2a buffers reclaim the KV that DCP buys. Compose only to measure. a2a backend is set when `--moe-a2a-backend` is set.
 
-No cell has a serving round in this exact shape — treat them as starting points to verify.
+Outside the two verified B300 1×8 `Unified` cells, no cell has a serving round in this exact shape — treat those as starting points to verify.
 
 <a id="amd-env" />
 

docs/src/snippets/configs/moonshotai/kimi-k3-benchmarks.jsx

@@ -19,4 +19,76 @@ export const benchmarks = [
   { match: { hw: "gb200", pdMode: "unified", strategy: "low-latency" } },
   { match: { hw: "gb200", pdMode: "unified", strategy: "balanced"    } },
   { match: { hw: "gb200", pdMode: "unified", strategy: "high-throughput"    } },
+  {
+    match: { hw: "b300", pdMode: "unified", strategy: "low-latency", quant: "mxfp4", spec: "none" },
+    sglang_version: "v0.5.18 @ 71de97b2",
+    speed: [
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 1 },
+        ttft_ms: 378, tpot_ms: 8.51, tokens_per_sec_per_gpu: 127 },
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 16 },
+        ttft_ms: 3539, tpot_ms: 19.47, tokens_per_sec_per_gpu: 785 },
+    ],
+  },
+  {
+    match: { hw: "b300", pdMode: "unified", strategy: "low-latency", quant: "mxfp4", spec: "dspark" },
+    sglang_version: "v0.5.18 @ 71de97b2",
+    speed: [
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 1 },
+        ttft_ms: 389, tpot_ms: 2.84, tokens_per_sec_per_gpu: 351 },
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 16 },
+        ttft_ms: 3942, tpot_ms: 9.88, tokens_per_sec_per_gpu: 1319 },
+    ],
+  },
+  {
+    match: { hw: "b300", pdMode: "unified", strategy: "low-latency", quant: "nvfp4", spec: "none" },
+    sglang_version: "v0.5.18 @ 71de97b2",
+    speed: [
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 1 },
+        ttft_ms: 369, tpot_ms: 10.12, tokens_per_sec_per_gpu: 107 },
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 16 },
+        ttft_ms: 3387, tpot_ms: 20.94, tokens_per_sec_per_gpu: 742 },
+    ],
+  },
+  {
+    match: { hw: "b300", pdMode: "unified", strategy: "low-latency", quant: "nvfp4", spec: "dspark" },
+    sglang_version: "v0.5.18 @ 71de97b2",
+    speed: [
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 1 },
+        ttft_ms: 380, tpot_ms: 3.24, tokens_per_sec_per_gpu: 313 },
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 16 },
+        ttft_ms: 3765, tpot_ms: 9.77, tokens_per_sec_per_gpu: 1345 },
+    ],
+  },
+  {
+    match: { hw: "b300", pdMode: "unified", strategy: "balanced", quant: "mxfp4", spec: "none" },
+    sglang_version: "v0.5.18 @ 71de97b2",
+    speed: [
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 64 },
+        ttft_ms: 11635, tpot_ms: 40.19, tokens_per_sec_per_gpu: 1395 },
+    ],
+  },
+  {
+    match: { hw: "b300", pdMode: "unified", strategy: "balanced", quant: "mxfp4", spec: "dspark" },
+    sglang_version: "v0.5.18 @ 71de97b2",
+    speed: [
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 64 },
+        ttft_ms: 12038, tpot_ms: 24.47, tokens_per_sec_per_gpu: 1987 },
+    ],
+  },
+  {
+    match: { hw: "b300", pdMode: "unified", strategy: "balanced", quant: "nvfp4", spec: "none" },
+    sglang_version: "v0.5.18 @ 71de97b2",
+    speed: [
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 64 },
+        ttft_ms: 11063, tpot_ms: 41.55, tokens_per_sec_per_gpu: 1373 },
+    ],
+  },
+  {
+    match: { hw: "b300", pdMode: "unified", strategy: "balanced", quant: "nvfp4", spec: "dspark" },
+    sglang_version: "v0.5.18 @ 71de97b2",
+    speed: [
+      { workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 64 },
+        ttft_ms: 11664, tpot_ms: 22.17, tokens_per_sec_per_gpu: 1946 },
+    ],
+  },
 ];

docs/src/snippets/configs/moonshotai/kimi-k3.jsx

@@ -454,7 +454,7 @@ export const config = {
   --dataset-name {{DATASET}} \\
   --random-input-len {{ISL}} --random-output-len {{OSL}} --random-range-ratio 1.0 \\
   --num-prompts {{NUM_PROMPTS}} --max-concurrency {{MAX_CONCURRENCY}} \\
-  --flush-cache`,
+  --warmup-requests 64 --flush-cache`,
     // num_prompts = 5 × concurrency (measured floor 16).
     numPromptsByConc: { 1: 16, 16: 80, 64: 320, 256: 1280, 1024: 5120 },
   },
@@ -1013,8 +1013,7 @@ export const config = {
     {
       match: { hw: "b300", pdMode: "unified", strategy: "low-latency" },
       nnodes: 1,
-      verified: false,
+      verified: true,
-      verificationStatus: "in-progress",
       env: [],
       // No --enable-symm-mem: it makes the fused all-reduce auto-probe skip.
       flags: [
@@ -1031,8 +1030,7 @@ export const config = {
     {
       match: { hw: "b300", pdMode: "unified", strategy: "balanced" },
       nnodes: 1,
-      verified: false,
+      verified: true,
-      verificationStatus: "in-progress",
       env: [],
       flags: [
         "--trust-remote-code",