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 53. 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 24.7. The single biggest benchmark swing on the page is SWE-bench Verified, 83 to 22.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for Gemini 3.1 Flash-Lite. That is roughly 375.0x on output cost alone. GPT-5.2 Pro is the reasoning model in the pair, while Gemini 3.1 Flash-Lite 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. Gemini 3.1 Flash-Lite gives you the larger context window at 1M, compared with 400K for GPT-5.2 Pro.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. Gemini 3.1 Flash-Lite only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
GPT-5.2 Pro
85.9
Gemini 3.1 Flash-Lite
49.2
GPT-5.2 Pro
84.8
Gemini 3.1 Flash-Lite
24.7
GPT-5.2 Pro
96
Gemini 3.1 Flash-Lite
73.1
GPT-5.2 Pro
95.2
Gemini 3.1 Flash-Lite
65.8
GPT-5.2 Pro
81.5
Gemini 3.1 Flash-Lite
45.3
GPT-5.2 Pro
95
Gemini 3.1 Flash-Lite
79
GPT-5.2 Pro
93.4
Gemini 3.1 Flash-Lite
69.8
GPT-5.2 Pro
98.2
Gemini 3.1 Flash-Lite
66.1
GPT-5.2 Pro is ahead overall, 90 to 53. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 83 and 22.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 45.3. Inside this category, HLE 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 24.7. Inside this category, SWE-bench Verified 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 66.1. 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 65.8. 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 49.2. 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 73.1. Inside this category, OfficeQA 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 79. 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 69.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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