LLM Inference Benchmark Explorer

GLM-4.7 on DGX B300 — FP8, vLLM, TP2 inference benchmark

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ModelGLM-4.7
Parameters358B
Intelligence Index22.2
Agentic Index—
DeviceDGX B300
QuantizationFP8
Max C32+
Chat Capacity42
Agentic Capacity10
TP2
DP—
PP—
EnginevLLM
Speculative Decoding—
CTTFT (ms)TPS (tok/s)Status
15380.40PASS
27684.93PASS
46872.46PASS
87958.26PASS
1657139.63PASS
3264233.11PASS

In OpenZeka's measurement, GLM-4.7 (358B parameters), served in FP8 format with vLLM on DGX B300 (TP=2), reached a generation speed of 80.4 tok/s per request and a time to first token (TTFT) of 53 ms with a single request.

Considering the speed targets and the available KV cache capacity, the estimated capacity is 42 users for chat use and 10 for agentic use. The realistic capacity will likely fall between these two values. In scenarios dominated by coding, tool use, long workflows and multi-agent use, capacity approaches the agentic estimate; where shorter interactions, standard conversations and lighter tasks dominate, it approaches the chat estimate.

Notes: 2 GPU

Intelligence Index and Agentic Index values are published by Artificial Analysis and are reproduced here with attribution.