Update GLM-5.2 NVFP4 B200/B300 for AgentX HiCache (#35368)
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@@ -269,3 +269,33 @@ When deploying with PD Disaggregation, the prefill node can choose to enable [La
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--cp-strategy interleave \
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```
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With LayerSplit, the kv cache on each rank can be sharded over the CP attention group, and prefetched when necessary. This can reduce kv cache memory by up to 75%, thus increasing the throughput on prefill side.
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### 3.6 Agentic Long-Context with HiCache DRAM Offload (NVFP4, MTP)
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**B300 (TP8):**
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```bash Command
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python3 -m sglang.launch_server \
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--model-path nvidia/GLM-5.2-NVFP4 \
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--trust-remote-code \
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--tp 8 \
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--ep-size 1 \
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--quantization modelopt_fp4 \
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--kv-cache-dtype fp8_e4m3 \
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--bf16-gemm-backend cutedsl \
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--max-prefill-tokens 8192 \
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--chunked-prefill-size 8192 \
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--mem-fraction-static 0.85 \
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--tool-call-parser glm47 \
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--reasoning-parser glm45 \
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--speculative-algorithm EAGLE \
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--speculative-num-steps 3 \
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--speculative-eagle-topk 1 \
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--speculative-num-draft-tokens 4 \
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--enable-hierarchical-cache \
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--hicache-size 270 \
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--hicache-write-policy write_back \
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--hicache-io-backend direct \
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--hicache-mem-layout page_first_direct
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```
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**B200 (TP8):** same command, with `--mem-fraction-static 0.83` and `--hicache-size 169`. Lower concurrency (c1/c4/c8) uses `--hicache-ratio 0.75` instead.
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