Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V3
36
GPT-5.2
81
Pick GPT-5.2 if you want the stronger benchmark profile. DeepSeek V3 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.
Coding
+25.5 difference
Knowledge
+22.4 difference
DeepSeek V3
GPT-5.2
$0.27 / $1.1
$1.75 / $14
N/A
73 t/s
N/A
130.34s
128K
400K
Pick GPT-5.2 if you want the stronger benchmark profile. DeepSeek V3 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 is clearly ahead on the provisional aggregate, 81 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in coding, where it averages 64.7 against 39.2. The single biggest benchmark swing on the page is SWE-bench Verified, 42% to 80%.
GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek V3. That is roughly 12.7x on output cost alone. GPT-5.2 is the reasoning model in the pair, while DeepSeek V3 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 gives you the larger context window at 400K, compared with 128K for DeepSeek V3.
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 81 to 36. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 42% and 80%.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 70. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for coding in this comparison, averaging 64.7 versus 39.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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