All model and GPU pairings
Muse Spark Open 816BNVIDIA Hopper

Running Muse Spark Open on H100

Quick answer

Muse Spark Open runs on H100: 5 benchmarked configs so far. See the interactivity ladder below for measured operating points.

Benchmarked configs

5

Serving engines

SGLang

Precisions

fp4

Run dates

2026-10-16 β†’ 2026-10-16

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--SGLangfp4
50 tok/s--SGLangfp4
75 tok/s--SGLangfp4
100 tok/s--SGLangfp4
150 tok/s--SGLangfp4
200 tok/s--SGLangfp4

Frequently asked questions

How fast is Muse Spark Open on H100?
The InferenceX fleet has 5 benchmarked configs for this pairing; see the interactivity ladder above for the operating points reached so far.
How much does it cost to serve Muse Spark Open on H100?
Cost per million tokens is derived from measured throughput and $/GPU/hr rates from the SemiAnalysis AI Cloud TCO model; it appears once this pairing reaches the primary interactivity tier.
Which serving engines run Muse Spark Open on H100?
The runs behind this page used SGLang in FP4. Engines are rebuilt and re-benchmarked continuously, so the best config can change between visits.
How are these Muse Spark Open numbers measured?
Every number is measured on real H100 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 2026-10-16. The same derivation powers the InferenceX overview leaderboard.

Explore the data