Grok 3 Mini vs LFM2.5-350M

Pick Grok 3 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.

Grok 3 Mini is clearly ahead on the aggregate, 49 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Grok 3 Mini's sharpest advantage is in knowledge, where it averages 59.8 against 23.8. The single biggest benchmark swing on the page is MMLU-Pro, 78.9% to 20.0%.

Grok 3 Mini is also the more expensive model on tokens at $0.30 input / $0.50 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. Grok 3 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. Grok 3 Mini gives you the larger context window at 128K, compared with 32K for LFM2.5-350M.