Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-4.5-Air
35
1/8 categoriesLFM2.5-350M
~39
Winner · 0/8 categoriesGLM-4.5-Air· LFM2.5-350M
Pick LFM2.5-350M if you want the stronger benchmark profile. GLM-4.5-Air only becomes the better choice if knowledge is the priority or you need the larger 128K context window.
LFM2.5-350M is clearly ahead on the aggregate, 39 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-4.5-Air 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 | GLM-4.5-Air | LFM2.5-350M |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 28% | — |
| OSWorld-Verified | 28% | — |
| Coding | ||
| HumanEval | 27% | — |
| SWE-bench Verified | 15% | — |
| LiveCodeBench | 15% | — |
| SWE-bench Pro | 14% | — |
| SWE-Rebench | 38.3% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 36% | — |
| OfficeQA Pro | 44% | — |
| Reasoning | ||
| MuSR | 31% | — |
| BBH | 63% | — |
| LongBench v2 | 47% | — |
| MRCRv2 | 51% | — |
| KnowledgeGLM-4.5-Air wins | ||
| MMLU | 35% | — |
| GPQA | 34% | 30.6% |
| SuperGPQA | 32% | — |
| MMLU-Pro | 51% | 20.0% |
| HLE | 4% | — |
| FrontierScience | 37% | — |
| SimpleQA | 33% | — |
| Instruction Following | ||
| IFEval | — | 77.0% |
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| AIME 2023 | 35% | — |
| AIME 2024 | 37% | — |
| AIME 2025 | 36% | — |
| HMMT Feb 2023 | 31% | — |
| HMMT Feb 2024 | 33% | — |
| HMMT Feb 2025 | 32% | — |
| BRUMO 2025 | 34% | — |
LFM2.5-350M is ahead overall, 39 to 35. The biggest single separator in this matchup is MMLU-Pro, where the scores are 51% and 20.0%.
GLM-4.5-Air has the edge for knowledge tasks in this comparison, averaging 31 versus 23.8. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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