Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
LFM2.5-350M
~39
0/8 categoriesQwen3 235B 2507 (Reasoning)
55
Winner · 2/8 categoriesLFM2.5-350M· Qwen3 235B 2507 (Reasoning)
Pick Qwen3 235B 2507 (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.
Qwen3 235B 2507 (Reasoning) is clearly ahead on the aggregate, 55 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3 235B 2507 (Reasoning)'s sharpest advantage is in knowledge, where it averages 50 against 23.8. The single biggest benchmark swing on the page is MMLU-Pro, 20.0% to 84.4%.
Qwen3 235B 2507 (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. Qwen3 235B 2507 (Reasoning) gives you the larger context window at 128K, 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 | Qwen3 235B 2507 (Reasoning) |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 47% |
| BrowseComp | — | 48% |
| OSWorld-Verified | — | 43% |
| Coding | ||
| HumanEval | — | 32% |
| SWE-bench Verified | — | 16% |
| LiveCodeBench | — | 74.1% |
| SWE-bench Pro | — | 29% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 38% |
| OfficeQA Pro | — | 47% |
| Reasoning | ||
| MuSR | — | 36% |
| BBH | — | 63% |
| LongBench v2 | — | 58% |
| MRCRv2 | — | 58% |
| KnowledgeQwen3 235B 2507 (Reasoning) wins | ||
| GPQA | 30.6% | 81.1% |
| MMLU-Pro | 20.0% | 84.4% |
| MMLU | — | 40% |
| SuperGPQA | — | 64.9% |
| HLE | — | 6% |
| FrontierScience | — | 42% |
| SimpleQA | — | 38% |
| Instruction FollowingQwen3 235B 2507 (Reasoning) wins | ||
| IFEval | 77.0% | 87.8% |
| Multilingual | ||
| MGSM | — | 62% |
| MMLU-ProX | — | 81% |
| Mathematics | ||
| AIME 2023 | — | 40% |
| AIME 2024 | — | 42% |
| AIME 2025 | — | 92.3% |
| HMMT Feb 2023 | — | 36% |
| HMMT Feb 2024 | — | 38% |
| HMMT Feb 2025 | — | 37% |
| BRUMO 2025 | — | 39% |
| MATH-500 | — | 60% |
Qwen3 235B 2507 (Reasoning) is ahead overall, 55 to 39. The biggest single separator in this matchup is MMLU-Pro, where the scores are 20.0% and 84.4%.
Qwen3 235B 2507 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 50 versus 23.8. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Qwen3 235B 2507 (Reasoning) has the edge for instruction following in this comparison, averaging 87.8 versus 77. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.