All model and GPU pairings
GLM 5/5.1NVIDIA Hopper

Running GLM-5 on H200

Quick answer

GLM-5 sustains 572 tokens/s per GPU on H200 at 50 tokens/s per user, which works out to $0.59 per million tokens at hyperscaler pricing, served by SGLang. Fastest measured TTFT: 0.2 ms; fastest TPOT: 0.0 ms (each the best across all configs, not one run).

Benchmarked configs

25

Serving engines

SGLang

Precisions

fp8

Run dates

2026-03-192026-05-19

Throughput at every interactivity target

Serving is a trade-off: push more concurrent users through a GPU and each user's tokens arrive slower. The ladder below reads the measured frontier at each per-user speed target on a single-turn chat workload (8k input / 1k output), using the best engine and precision at that point.

Per-user targetTokens/s per GPU$ / 1M tokensEnginePrecision
30 tok/s788$0.43SGLangfp8
50 tok/s572$0.59SGLangfp8
75 tok/s395$0.86SGLangfp8
100 tok/s--SGLangfp8
150 tok/s--SGLangfp8
200 tok/s--SGLangfp8

What serving actually costs

Converting the 50 tokens/s per user operating point to $ per million total tokens across rental pricing tiers from the SemiAnalysis AI Cloud TCO model.

Pricing tier$ / GPU / hr$ / 1M tokens
Hyperscaler$1.22$0.59
Neocloud$1.59$0.77
Retail$2.05$0.99

Frequently asked questions

How fast is GLM-5 on H200?
At an interactivity target of 50 tokens/s per user on a single-turn chat workload (8k input / 1k output), H200 sustains 572 tokens/s per GPU serving GLM-5 with SGLang in FP8. Peak measured throughput across all configs is 852 tokens/s per GPU.
How much does it cost to serve GLM-5 on H200?
$0.59 per million total tokens at hyperscaler $/GPU/hr pricing, at 50 tokens/s per user. Neocloud and retail rental tiers are tabulated above; slower interactivity targets lower the cost further.
Which serving engines run GLM-5 on H200?
The runs behind this page used SGLang in FP8. Engines are rebuilt and re-benchmarked continuously, so the best config can change between visits.
How are these GLM-5 numbers measured?
Every number is measured on real H200 hardware by the InferenceX fleet, sweeping concurrency on a single-turn chat workload (8k input / 1k output) to trace the throughput-versus-interactivity frontier; the newest run landed on 2026-05-19. The same derivation powers the InferenceX overview leaderboard.

Explore the data