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 64. 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 43.2. The single biggest benchmark swing on the page is LiveCodeBench, 74 to 39.
GPT-5.2 Instant is the reasoning model in the pair, while DeepSeek V3.2 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.
Pick GPT-5.2 Instant if you want the stronger benchmark profile. DeepSeek V3.2 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
DeepSeek V3.2
58.8
GPT-5.2 Instant
75.5
DeepSeek V3.2
43.2
GPT-5.2 Instant
93.1
DeepSeek V3.2
66
GPT-5.2 Instant
90.9
DeepSeek V3.2
75.3
GPT-5.2 Instant
79.8
DeepSeek V3.2
60
GPT-5.2 Instant
95
DeepSeek V3.2
85
GPT-5.2 Instant
94.4
DeepSeek V3.2
82.1
GPT-5.2 Instant
97.2
DeepSeek V3.2
82.1
GPT-5.2 Instant is ahead overall, 85 to 64. The biggest single separator in this matchup is LiveCodeBench, where the scores are 74 and 39.
GPT-5.2 Instant has the edge for knowledge tasks in this comparison, averaging 79.8 versus 60. 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 43.2. 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 82.1. Inside this category, MATH-500 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 75.3. Inside this category, LongBench v2 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 58.8. 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 66. 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 85. 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 82.1. 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.