DeepSeek V3.2 vs GPT-5.3 Codex

Pick GPT-5.3 Codex if you want the stronger benchmark profile. DeepSeek V3.2 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-5.3 Codex is clearly ahead on the provisional aggregate, 89 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GPT-5.3 Codex's sharpest advantage is in coding, where it averages 63.1 against 60.9. The single biggest benchmark swing on the page is SWE-Rebench, 60.9% to 58.2%.

GPT-5.3 Codex is also the more expensive model on tokens at $2.50 input / $10.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for DeepSeek V3.2. That is roughly Infinityx on output cost alone. GPT-5.3 Codex 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. GPT-5.3 Codex gives you the larger context window at 400K, compared with 128K for DeepSeek V3.2.