Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Pro is clearly ahead on the aggregate, 90 to 32. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2 Pro's sharpest advantage is in coding, where it averages 84.8 against 13.2. The single biggest benchmark swing on the page is SWE-bench Pro, 89 to 12.
GPT-5.2 Pro is the reasoning model in the pair, while Mistral 7B v0.3 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-5.2 Pro gives you the larger context window at 400K, compared with 32K for Mistral 7B v0.3.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. Mistral 7B v0.3 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.2 Pro
85.9
Mistral 7B v0.3
26.4
GPT-5.2 Pro
84.8
Mistral 7B v0.3
13.2
GPT-5.2 Pro
96
Mistral 7B v0.3
32.4
GPT-5.2 Pro
95.2
Mistral 7B v0.3
36.1
GPT-5.2 Pro
81.5
Mistral 7B v0.3
30
GPT-5.2 Pro
95
Mistral 7B v0.3
68
GPT-5.2 Pro
93.4
Mistral 7B v0.3
60.7
GPT-5.2 Pro
98.2
Mistral 7B v0.3
43
GPT-5.2 Pro is ahead overall, 90 to 32. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 89 and 12.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 30. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for coding in this comparison, averaging 84.8 versus 13.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for math in this comparison, averaging 98.2 versus 43. Inside this category, HMMT Feb 2023 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for reasoning in this comparison, averaging 95.2 versus 36.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for agentic tasks in this comparison, averaging 85.9 versus 26.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 96 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for instruction following in this comparison, averaging 95 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multilingual tasks in this comparison, averaging 93.4 versus 60.7. Inside this category, MGSM 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.