Introducing Mercury, the first commercial-scale diffusion large language model (Inception blog) Feb 26, 2025
- HumanEval 90
- MBPP 76.6
- EvalPlus 80.4
- MultiPL-E 76.2
- LiveCodeBench (version not stated) 25
- BigCodeBench 45.5
Mercury Coder Small places in the top three on EvalPlus.
Closed weights Flagship
Its best score on each benchmark, and where that ranks among every model with a score there. We rank each model once, at its best setting.
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| HumanEval | 90% | #13 of 101 | Lab model card | |
| MBPP | 76.6% | #30 of 71 | Lab model card | |
| MultiPL-E | 76.2% | #8 of 18 | Lab model card | |
| EvalPlus | 80.4% | #3 of 6 | Lab model card | |
| BigCodeBench | 45.5% | #10 of 14 | Lab model card | |
| LiveCodeBench | 25% | #46 of 54 | Lab model card | |
| HumanEval Infilling | 84.8% | #1 of 1 | Lab model card |
The Self-Reported Index fits one score to the 5 capability results Inception Labs reported for this model, on the scale of the Epoch Capabilities Index. Labs choose which benchmarks to show and how to run them, so read it as the lab's claim, not an independent measurement. The 90% interval runs from 117.8 to 126.6. How we compute it.
The benchmarks the lab chose to headline, with the scores it gave.
Every result in the longer documents the lab published with it. 1 of them isn't in the launch post.