Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Instant is clearly ahead on the aggregate, 85 to 48. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2 Instant's sharpest advantage is in coding, where it averages 75.5 against 25.8. The single biggest benchmark swing on the page is MMMU-Pro, 94 to 42.
GPT-5.2 Instant is the reasoning model in the pair, while Mistral 8x7B 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 Instant gives you the larger context window at 128K, compared with 32K for Mistral 8x7B.
Pick GPT-5.2 Instant if you want the stronger benchmark profile. Mistral 8x7B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.2 Instant
79.6
Mistral 8x7B
41.1
GPT-5.2 Instant
75.5
Mistral 8x7B
25.8
GPT-5.2 Instant
93.1
Mistral 8x7B
48.3
GPT-5.2 Instant
90.9
Mistral 8x7B
60.3
GPT-5.2 Instant
79.8
Mistral 8x7B
48.4
GPT-5.2 Instant
95
Mistral 8x7B
78
GPT-5.2 Instant
94.4
Mistral 8x7B
72.1
GPT-5.2 Instant
97.2
Mistral 8x7B
68.1
GPT-5.2 Instant is ahead overall, 85 to 48. The biggest single separator in this matchup is MMMU-Pro, where the scores are 94 and 42.
GPT-5.2 Instant has the edge for knowledge tasks in this comparison, averaging 79.8 versus 48.4. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for coding in this comparison, averaging 75.5 versus 25.8. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for math in this comparison, averaging 97.2 versus 68.1. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for reasoning in this comparison, averaging 90.9 versus 60.3. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for agentic tasks in this comparison, averaging 79.6 versus 41.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for multimodal and grounded tasks in this comparison, averaging 93.1 versus 48.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for instruction following in this comparison, averaging 95 versus 78. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for multilingual tasks in this comparison, averaging 94.4 versus 72.1. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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