Running GLM-5.2 on MI355X
Quick answer
GLM-5.2 sustains 10,382 tokens/s per GPU on MI355X at 50 tokens/s per user, which works out to $0.040 per million tokens at hyperscaler pricing, served by SGLang. Fastest measured TTFT: 0.4 ms; fastest TPOT: 0.0 ms (each the best across all configs, not one run).
Benchmarked configs
17
Serving engines
ATOM¹, SGLang
Precisions
fp4
Run dates
2026-08-11 → 2026-08-19
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 the AgentX agentic coding workload, using the best engine and precision at that point.
| Per-user target | Tokens/s per GPU | $ / 1M tokens | Engine | Precision |
|---|---|---|---|---|
| 30 tok/s | - | - | SGLang | fp4 |
| 50 tok/s | 10,382 | $0.040 | SGLang | fp4 |
| 75 tok/s | 5,522 | $0.075 | SGLang | fp4 |
| 100 tok/s | 3,095 | $0.13 | SGLang | fp4 |
| 150 tok/s | - | - | SGLang | fp4 |
| 200 tok/s | - | - | SGLang | fp4 |
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 | $1.50 | $0.040 |
| Neocloud | $2.09 | $0.056 |
| Retail | $2.10 | $0.056 |
Frequently asked questions
- How fast is GLM-5.2 on MI355X?
- At an interactivity target of 50 tokens/s per user on the AgentX agentic coding workload, MI355X sustains 10,382 tokens/s per GPU serving GLM-5.2 with SGLang in FP4. Peak measured throughput across all configs is 11,956 tokens/s per GPU.
- How much does it cost to serve GLM-5.2 on MI355X?
- $0.040 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-5.2 on MI355X?
- The runs behind this page used ATOM¹, SGLang in FP4. Engines are rebuilt and re-benchmarked continuously, so the best config can change between visits.
- How are these GLM-5.2 numbers measured?
- Every number is measured on real MI355X 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 2026-08-19. The same derivation powers the InferenceX overview leaderboard.