Laguna S 2.1
Collection
Our most capable model to date, designed for long-horizon work. • 11 items • Updated • 13
Use on OpenRouter · Use on Vercel AI Gateway · Release blog post
poolside/Laguna-S-2.1-DFlash-FP8
DFlash speculator for the FP8 target poolside/Laguna-S-2.1-FP8. The speculator is a 6-layer Laguna-style draft model (BF16); pair it with the FP8 base for lower-latency serving via speculative decoding.
Trained: e0630_rhiemann_baseline SFT, DFlash Stage-2, 15k steps. Recommended
serving setting: num_speculative_tokens=7.
DFlash upstream support is in progress (vLLM #46853, SGLang #29446, TRT-LLM #15666). Use
poolside/Laguna-S-2.1-FP8 as the target model.
Benchmarks
Measured with TP=2, temperature=0, and num_speculative_tokens=15.
Throughput speedup
| Concurrency | GSM8K | MATH-500 | HumanEval | MBPP | MT-Bench |
|---|---|---|---|---|---|
| 1 | 3.179x | 2.938x | 3.269x | 2.380x | 2.603x |
| 4 | 2.614x | 2.423x | 2.691x | 1.963x | 2.090x |
| 8 | 2.666x | 2.410x | 2.803x | 1.962x | 2.230x |
| 16 | 2.618x | 2.364x | 2.866x | 2.031x | 2.302x |
Acceptance length
| Concurrency | GSM8K | MATH-500 | HumanEval | MBPP | MT-Bench |
|---|---|---|---|---|---|
| 1 | 5.748 | 5.197 | 5.889 | 4.247 | 4.663 |
| 4 | 5.765 | 5.212 | 5.882 | 4.218 | 4.411 |
| 8 | 5.863 | 5.199 | 6.094 | 4.178 | 4.572 |
| 16 | 5.787 | 5.161 | 6.144 | 4.291 | 4.600 |
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