Compile. Benchmark.
Deploy.
We compare Muna-compiled models against conventional deployments across artifact size, cold starts, time to first token, and decode throughput. Every number below is derived from raw result files you can download, and every run can be reproduced from a public script.
Gemma 4 26B A4B
chat@google/gemma-4-26b-a4b-it
NVIDIA B200 · May 2026 · vs SGLang
- compiled model code size
- 96MB
- compiled model code size
- artifact pull, vs 25.8GB · 193,735 files
- 760MB · 5 files
- artifact pull, vs 25.8GB · 193,735 files
- CTTFT @p90 · Muna (bare metal)
- 6.3s
- CTTFT @p90 · Muna (bare metal)
- lower median CTTFT vs SGLang (Modal)
- 18×
- lower median CTTFT vs SGLang (Modal)
- TTFT @16k-token prompts
- 147ms
- TTFT @16k-token prompts
- tok/s across prompt categories
- 206–593
- tok/s across prompt categories