Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
LFM2.5-350M
~39
0/8 categoriesMistral Small 4 (Reasoning)
~64
Winner · 1/8 categoriesLFM2.5-350M· Mistral Small 4 (Reasoning)
Pick Mistral Small 4 (Reasoning) if you want the stronger benchmark profile. LFM2.5-350M only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Mistral Small 4 (Reasoning) is clearly ahead on the aggregate, 64 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mistral Small 4 (Reasoning)'s sharpest advantage is in knowledge, where it averages 75.6 against 23.8. The single biggest benchmark swing on the page is MMLU-Pro, 20.0% to 78%.
Mistral Small 4 (Reasoning) is the reasoning model in the pair, while LFM2.5-350M is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Mistral Small 4 (Reasoning) gives you the larger context window at 256K, compared with 32K for LFM2.5-350M.
BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.
Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.
| Benchmark | LFM2.5-350M | Mistral Small 4 (Reasoning) |
|---|---|---|
| Agentic | ||
| Coming soon | ||
| Coding | ||
| LiveCodeBench | — | 63.6% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 60% |
| Reasoning | ||
| Coming soon | ||
| KnowledgeMistral Small 4 (Reasoning) wins | ||
| GPQA | 30.6% | 71.2% |
| MMLU-Pro | 20.0% | 78% |
| Instruction Following | ||
| IFEval | 77.0% | — |
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| AIME 2025 | — | 83.8% |
Mistral Small 4 (Reasoning) is ahead overall, 64 to 39. The biggest single separator in this matchup is MMLU-Pro, where the scores are 20.0% and 78%.
Mistral Small 4 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 75.6 versus 23.8. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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