docs: add B200 NVFP4 recipes + benchmarks to GLM-5.2 cookbook (#29674)
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
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Claude Opus 4.8
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@@ -102,4 +102,36 @@ export const benchmarks = [
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{ match: { hw: "gb300", variant: "default", quant: "bf16", strategy: "low-latency", nodes: "multi-2" } },
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{ match: { hw: "gb300", variant: "default", quant: "bf16", strategy: "balanced", nodes: "multi-2" } },
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{ match: { hw: "gb300", variant: "default", quant: "bf16", strategy: "high-throughput", nodes: "multi-2" } },
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// ---- B200 + NVFP4 ---- (8-GPU single node, TP8; nvidia/GLM-5.2-NVFP4 via --quantization modelopt_fp4,
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// measured on the lmsysorg/sglang:dev-glm52-nvfp4 preview image, flush-cache every run.
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// ttft_ms/tpot_ms are P50; tokens_per_sec_per_gpu = output tok/s/GPU.
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// balanced & high-throughput add DP-Attention (dp8); low-latency uses MTP 5-1-6, balanced MTP 2-1-3.)
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{
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match: { hw: "b200", variant: "default", quant: "nvfp4", strategy: "low-latency", nodes: "single" },
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sglang_version: "dev-glm52-nvfp4",
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speed: [
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{ workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 1 },
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ttft_ms: 295, tpot_ms: 1.85, tokens_per_sec_per_gpu: 58.6 },
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{ workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 16 },
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ttft_ms: 2491, tpot_ms: 5.43, tokens_per_sec_per_gpu: 254.3 },
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],
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},
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{
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match: { hw: "b200", variant: "default", quant: "nvfp4", strategy: "balanced", nodes: "single" },
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sglang_version: "dev-glm52-nvfp4",
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speed: [
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{ workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 64 },
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ttft_ms: 5837, tpot_ms: 12.70, tokens_per_sec_per_gpu: 418.9 },
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{ workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 256 },
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ttft_ms: 16736, tpot_ms: 30.00, tokens_per_sec_per_gpu: 593.7 },
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],
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},
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{
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match: { hw: "b200", variant: "default", quant: "nvfp4", strategy: "high-throughput", nodes: "single" },
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sglang_version: "dev-glm52-nvfp4",
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speed: [
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{ workload: { dataset: "random", isl: 8192, osl: 1024, max_concurrency: 1024 },
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ttft_ms: 130174, tpot_ms: 67.12, tokens_per_sec_per_gpu: 589.4 },
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],
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},
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];
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@@ -94,6 +94,7 @@ sgl-eval run aime25 \\
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gb300: "lmsysorg/sglang:latest",
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b300: "lmsysorg/sglang:latest",
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// NVFP4 needs the dev image with modelopt_fp4 support (per-quant override).
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"b200|nvfp4": "lmsysorg/sglang:dev-glm52-nvfp4",
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"b300|nvfp4": "lmsysorg/sglang:dev-glm52-nvfp4",
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"gb300|nvfp4": "lmsysorg/sglang:dev-glm52-nvfp4",
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},
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@@ -613,11 +614,71 @@ sgl-eval run aime25 \\
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},
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// ====================================================================
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// NVFP4 (Blackwell Ultra) — nvidia/GLM-5.2-NVFP4 (Model Optimizer). TP4.
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// B300: low-latency + balanced (the 4-GPU GB300 node fits the ~381 GB build).
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// GB300: low-latency / balanced / high-throughput measured on a single 4xGB300
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// node — balanced & high-throughput add DP-Attention (dp4); low-latency uses MTP 5-1-6.
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// NVFP4 — nvidia/GLM-5.2-NVFP4 (Model Optimizer).
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// B200: 8-GPU single node, TP8 (low-latency / balanced / high-throughput); balanced &
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// high-throughput add DP-Attention (dp8). low-latency uses MTP 5-1-6, balanced MTP 2-1-3.
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// B300/GB300: 4-GPU single node, TP4 (the node fits the ~381 GB build); GB300 adds dp4 on
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// balanced & high-throughput. Blackwell NVFP4 measured on the dev-glm52-nvfp4 preview image.
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// ====================================================================
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{
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match: { hw: "b200", variant: "default", quant: "nvfp4", strategy: "low-latency", nodes: "single" },
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verified: true,
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env: [],
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flags: [
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"--model-path {{MODEL_NAME}}",
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"--tp 8",
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"--quantization modelopt_fp4",
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"--speculative-algorithm EAGLE",
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"--speculative-num-steps 5",
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"--speculative-eagle-topk 1",
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"--speculative-num-draft-tokens 6",
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"--chunked-prefill-size 8192",
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"--mem-fraction-static 0.85",
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"--host {{HOST_IP}}",
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"--port {{PORT}}",
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],
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},
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{
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match: { hw: "b200", variant: "default", quant: "nvfp4", strategy: "balanced", nodes: "single" },
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verified: true,
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env: [],
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flags: [
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"--model-path {{MODEL_NAME}}",
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"--tp 8",
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"--quantization modelopt_fp4",
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"--dp 8",
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"--enable-dp-attention",
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// Shorter draft (MTP 2-1-3) than low-latency's 5-1-6: at this concurrency the
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// verify overhead of a long draft outweighs the accept-length gain.
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"--speculative-algorithm EAGLE",
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"--speculative-num-steps 2",
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"--speculative-eagle-topk 1",
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"--speculative-num-draft-tokens 3",
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// Larger chunked-prefill (32768 → ~4096/rank under dp8) is the dominant balanced lever.
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"--chunked-prefill-size 32768",
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"--mem-fraction-static 0.92",
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"--max-running-requests 256",
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"--host {{HOST_IP}}",
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"--port {{PORT}}",
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],
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},
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{
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match: { hw: "b200", variant: "default", quant: "nvfp4", strategy: "high-throughput", nodes: "single" },
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verified: true,
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env: [],
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flags: [
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"--model-path {{MODEL_NAME}}",
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"--tp 8",
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"--quantization modelopt_fp4",
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"--dp 8",
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"--enable-dp-attention",
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"--chunked-prefill-size 32768",
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"--mem-fraction-static 0.92",
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"--max-running-requests 512",
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"--host {{HOST_IP}}",
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"--port {{PORT}}",
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],
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},
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{
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match: { hw: "b300", variant: "default", quant: "nvfp4", strategy: "low-latency", nodes: "single" },
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verified: true,
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