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 43. 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 15.7. The single biggest benchmark swing on the page is SWE-bench Pro, 89 to 17.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Llama 4 Maverick. That is roughly Infinityx on output cost alone. GPT-5.2 Pro is the reasoning model in the pair, while Llama 4 Maverick 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. Llama 4 Maverick 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. Llama 4 Maverick 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
Llama 4 Maverick
40.9
GPT-5.2 Pro
84.8
Llama 4 Maverick
15.7
GPT-5.2 Pro
96
Llama 4 Maverick
56.8
GPT-5.2 Pro
95.2
Llama 4 Maverick
54
GPT-5.2 Pro
81.5
Llama 4 Maverick
36.5
GPT-5.2 Pro
95
Llama 4 Maverick
68
GPT-5.2 Pro
93.4
Llama 4 Maverick
59.8
GPT-5.2 Pro
98.2
Llama 4 Maverick
51.3
GPT-5.2 Pro is ahead overall, 90 to 43. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 89 and 17.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 36.5. 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 15.7. 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 51.3. 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 54. 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 40.9. 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 56.8. 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 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 59.8. 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.