All model and GPU pairings
GLM 5.3 744BAMD CDNA 3

Running GLM-5.3 on MI325X

Quick answer

GLM-5.3 sustains 1,212 tokens/s per GPU on MI325X at 50 tokens/s per user, which works out to $0.25 per million tokens at hyperscaler pricing, served by SGLang. Fastest measured TTFT: 2.0 ms; fastest TPOT: 0.0 ms (each the best across all configs, not one run).

Benchmarked configs

7

Serving engines

SGLang

Precisions

fp8

Run dates

2026-09-25 β†’ 2026-09-25

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 the AgentX agentic coding workload, using the best engine and precision at that point.

Per-user targetTokens/s per GPU$ / 1M tokensEnginePrecision
30 tok/s--SGLangfp8
50 tok/s1,212$0.25SGLangfp8
75 tok/s--SGLangfp8
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
Owning at Large Hyperscaler Volume$1.10$0.25
Retail$1.60$0.37

Frequently asked questions

How fast is GLM-5.3 on MI325X?
At an interactivity target of 50 tokens/s per user on the AgentX agentic coding workload, MI325X sustains 1,212 tokens/s per GPU serving GLM-5.3 with SGLang in FP8. Peak measured throughput across all configs is 1,529 tokens/s per GPU.
How much does it cost to serve GLM-5.3 on MI325X?
$0.25 per million total tokens at large-hyperscaler-volume ownership $/GPU/hr pricing, at 50 tokens/s per user. The retail rental tier is tabulated above; slower interactivity targets lower the cost further.
Which serving engines run GLM-5.3 on MI325X?
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-5.3 numbers measured?
Every number is measured on real MI325X hardware by the InferenceX fleet, sweeping concurrency on the AgentX agentic coding workload to trace the throughput-versus-interactivity frontier; the newest run landed on 2026-09-25. The same derivation powers the InferenceX overview leaderboard.

Explore the data