- GPQA Diamond (± 0.83) 37.9
- MMLU-Pro (± 0.18) 49.6
- IFEval (± 0.35) 88.4
- IFBench (± 0.73) 44.9
- Multi-IF (± 0.09) 69.3
- GSM8K 85.6
- MATH-500 (± 0.72) 88
- AIME25 (± 1.81) 31.7
- BFCLv3 57
LFM2.5-1.2B-Thinking
LFM2.5-1.2B-Thinking.
9
Benchmarks with a score
0
Ranked first, out of five or more models
0
In the top three
Liquid AI Jan 2026
LFM2.5-1.2B-Thinking
Open weights Small
No Epoch Capabilities Index score yet
- IFBench 44.9% #64 /70
- MMLU-Pro 49.6% #140 /151
- AIME 2025 31.7% #138 /143
Where it ranks
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.
Knowledge and language
Math and science
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| GSM8K | 85.6% | #51 of 87 | Model card | |
| MATH-500 | 88% | #54 of 67 | Model card | |
| GPQA Diamond | 37.9% | #262 of 284 | Model card | |
| AIME 2025 | 31.7% | #138 of 143 | Model card |
Agents and tools
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| Berkeley Function Calling Leaderboard (BFCL) | 57% | #43 of 47 | Model card |
Its launch post
The benchmarks the lab chose to headline, with the scores it gave.