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 61. 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 44.2. The single biggest benchmark swing on the page is SWE-bench Pro, 89 to 46.
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 Nemotron 3 Super 120B A12B. That is roughly Infinityx on output cost alone. GPT-5.2 Pro is the reasoning model in the pair, while Nemotron 3 Super 120B A12B 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 256K for Nemotron 3 Super 120B A12B.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. Nemotron 3 Super 120B A12B only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.2 Pro
85.9
Nemotron 3 Super 120B A12B
55.3
GPT-5.2 Pro
84.8
Nemotron 3 Super 120B A12B
44.2
GPT-5.2 Pro
96
Nemotron 3 Super 120B A12B
60.4
GPT-5.2 Pro
95.2
Nemotron 3 Super 120B A12B
71.8
GPT-5.2 Pro
81.5
Nemotron 3 Super 120B A12B
55.8
GPT-5.2 Pro
95
Nemotron 3 Super 120B A12B
86
GPT-5.2 Pro
93.4
Nemotron 3 Super 120B A12B
81.5
GPT-5.2 Pro
98.2
Nemotron 3 Super 120B A12B
74.6
GPT-5.2 Pro is ahead overall, 90 to 61. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 89 and 46.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 55.8. 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 44.2. 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 74.6. 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 71.8. 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 55.3. 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 60.4. 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 86. 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 81.5. 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.