Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
o3-mini is clearly ahead on the aggregate, 56 to 50. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o3-mini's sharpest advantage is in knowledge, where it averages 82.1 against 43.8. The single biggest benchmark swing on the page is MMLU, 86.9 to 51.
o3-mini is the reasoning model in the pair, while GPT-OSS 120B 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. o3-mini gives you the larger context window at 200K, compared with 128K for GPT-OSS 120B.
Pick o3-mini if you want the stronger benchmark profile. GPT-OSS 120B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
o3-mini
82.1
GPT-OSS 120B
43.8
o3-mini
49.3
GPT-OSS 120B
32.3
o3-mini
87.3
GPT-OSS 120B
52.6
o3-mini
93.9
GPT-OSS 120B
79
o3-mini is ahead overall, 56 to 50. The biggest single separator in this matchup is MMLU, where the scores are 86.9 and 51.
o3-mini has the edge for knowledge tasks in this comparison, averaging 82.1 versus 43.8. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o3-mini has the edge for coding in this comparison, averaging 49.3 versus 32.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
o3-mini has the edge for math in this comparison, averaging 87.3 versus 52.6. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o3-mini has the edge for instruction following in this comparison, averaging 93.9 versus 79. 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.