Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.4 mini
68
Winner · 2/8 categoriesLFM2.5-350M
~39
0/8 categoriesGPT-5.4 mini· LFM2.5-350M
Pick GPT-5.4 mini if you want the stronger benchmark profile. LFM2.5-350M only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.4 mini is clearly ahead on the aggregate, 68 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 mini's sharpest advantage is in knowledge, where it averages 57.4 against 23.8. The single biggest benchmark swing on the page is GPQA, 88% to 30.6%.
GPT-5.4 mini is also the more expensive model on tokens at $0.75 input / $4.50 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2.5-350M. That is roughly Infinityx on output cost alone. GPT-5.4 mini 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. GPT-5.4 mini gives you the larger context window at 400K, 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 | GPT-5.4 mini | LFM2.5-350M |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 60% | — |
| OSWorld-Verified | 72.1% | — |
| MCP Atlas | 57.7% | — |
| Toolathlon | 42.9% | — |
| tau2-bench | 93.4% | — |
| Coding | ||
| SWE-bench Pro | 54.4% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 76.6% | — |
| MMMU-Pro w/ Python | 78% | — |
| OmniDocBench 1.5 | 0.1263 | — |
| Reasoning | ||
| MRCRv2 | 40.7% | — |
| MRCR v2 64K-128K | 47.7% | — |
| MRCR v2 128K-256K | 33.6% | — |
| Graphwalks BFS 128K | 76.3% | — |
| Graphwalks Parents 128K | 71.5% | — |
| KnowledgeGPT-5.4 mini wins | ||
| GPQA | 88% | 30.6% |
| HLE | 41.5% | — |
| HLE w/o tools | 28.2% | — |
| MMLU-Pro | — | 20.0% |
| Instruction FollowingGPT-5.4 mini wins | ||
| IFEval | 87.4% | 77.0% |
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| MATH-500 | 97.4% | — |
GPT-5.4 mini is ahead overall, 68 to 39. The biggest single separator in this matchup is GPQA, where the scores are 88% and 30.6%.
GPT-5.4 mini has the edge for knowledge tasks in this comparison, averaging 57.4 versus 23.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5.4 mini has the edge for instruction following in this comparison, averaging 87.4 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.