Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-5 (Reasoning)
82
Winner · 2/8 categoriesLFM2.5-350M
~39
0/8 categoriesGLM-5 (Reasoning)· LFM2.5-350M
Pick GLM-5 (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.
GLM-5 (Reasoning) is clearly ahead on the aggregate, 82 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5 (Reasoning)'s sharpest advantage is in knowledge, where it averages 73.7 against 23.8. The single biggest benchmark swing on the page is GPQA, 94% to 30.6%.
GLM-5 (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. GLM-5 (Reasoning) gives you the larger context window at 200K, 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-5 (Reasoning) | LFM2.5-350M |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 81% | — |
| BrowseComp | 80% | — |
| OSWorld-Verified | 74% | — |
| Coding | ||
| HumanEval | 88% | — |
| SWE-bench Verified | 62% | — |
| LiveCodeBench | 58% | — |
| SWE-bench Pro | 67% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 74% | — |
| OfficeQA Pro | 84% | — |
| Reasoning | ||
| MuSR | 90% | — |
| BBH | 91% | — |
| LongBench v2 | 86% | — |
| MRCRv2 | 87% | — |
| KnowledgeGLM-5 (Reasoning) wins | ||
| MMLU | 96% | — |
| GPQA | 94% | 30.6% |
| SuperGPQA | 92% | — |
| MMLU-Pro | 81% | 20.0% |
| HLE | 29% | — |
| FrontierScience | 83% | — |
| SimpleQA | 92% | — |
| Instruction FollowingGLM-5 (Reasoning) wins | ||
| IFEval | 92% | 77.0% |
| Multilingual | ||
| MGSM | 89% | — |
| MMLU-ProX | 85% | — |
| Mathematics | ||
| AIME 2023 | 98% | — |
| AIME 2024 | 99% | — |
| AIME 2025 | 98% | — |
| HMMT Feb 2023 | 94% | — |
| HMMT Feb 2024 | 96% | — |
| HMMT Feb 2025 | 95% | — |
| BRUMO 2025 | 96% | — |
| MATH-500 | 92% | — |
GLM-5 (Reasoning) is ahead overall, 82 to 39. The biggest single separator in this matchup is GPQA, where the scores are 94% and 30.6%.
GLM-5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 73.7 versus 23.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for instruction following in this comparison, averaging 92 versus 77. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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