Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o1-pro is clearly ahead on the aggregate, 45 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1-pro's sharpest advantage is in knowledge, where it averages 69.9 against 30. The single biggest benchmark swing on the page is AIME 2024, 86 to 35. Ministral 3 8B (Reasoning) does hit back in multilingual, so the answer changes if that is the part of the workload you care about most.
o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ministral 3 8B (Reasoning). That is roughly Infinityx on output cost alone. o1-pro gives you the larger context window at 200K, compared with 128K for Ministral 3 8B (Reasoning).
Pick o1-pro if you want the stronger benchmark profile. Ministral 3 8B (Reasoning) only becomes the better choice if multilingual is the priority or you want the cheaper token bill.
o1-pro
39.7
Ministral 3 8B (Reasoning)
38.5
o1-pro
23
Ministral 3 8B (Reasoning)
15.2
o1-pro
48.5
Ministral 3 8B (Reasoning)
33.4
o1-pro
56.2
Ministral 3 8B (Reasoning)
42.1
o1-pro
69.9
Ministral 3 8B (Reasoning)
30
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
o1-pro
52
Ministral 3 8B (Reasoning)
61.7
o1-pro
86
Ministral 3 8B (Reasoning)
47.8
o1-pro is ahead overall, 45 to 36. The biggest single separator in this matchup is AIME 2024, where the scores are 86 and 35.
o1-pro has the edge for knowledge tasks in this comparison, averaging 69.9 versus 30. Inside this category, GPQA is the benchmark that creates the most daylight between them.
o1-pro has the edge for coding in this comparison, averaging 23 versus 15.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
o1-pro has the edge for math in this comparison, averaging 86 versus 47.8. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o1-pro has the edge for reasoning in this comparison, averaging 56.2 versus 42.1. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
o1-pro has the edge for agentic tasks in this comparison, averaging 39.7 versus 38.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
o1-pro has the edge for multimodal and grounded tasks in this comparison, averaging 48.5 versus 33.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Ministral 3 8B (Reasoning) has the edge for multilingual tasks in this comparison, averaging 61.7 versus 52. Inside this category, MMLU-ProX 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.