Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.3 Codex is clearly ahead on the aggregate, 89 to 31. 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 87.3 against 7.2. The single biggest benchmark swing on the page is SWE-bench Pro, 90 to 6.
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 Ministral 3 3B (Reasoning). That is roughly Infinityx on output cost alone. GPT-5.3 Codex gives you the larger context window at 400K, compared with 128K for Ministral 3 3B (Reasoning).
Pick GPT-5.3 Codex if you want the stronger benchmark profile. Ministral 3 3B (Reasoning) only becomes the better choice if you want the cheaper token bill.
GPT-5.3 Codex
88.1
Ministral 3 3B (Reasoning)
34
GPT-5.3 Codex
87.3
Ministral 3 3B (Reasoning)
7.2
GPT-5.3 Codex
91.3
Ministral 3 3B (Reasoning)
30.4
GPT-5.3 Codex
93.7
Ministral 3 3B (Reasoning)
35.3
GPT-5.3 Codex
80.3
Ministral 3 3B (Reasoning)
25.2
GPT-5.3 Codex
93
Ministral 3 3B (Reasoning)
68
GPT-5.3 Codex
92.8
Ministral 3 3B (Reasoning)
59.7
GPT-5.3 Codex
97.7
Ministral 3 3B (Reasoning)
40.9
GPT-5.3 Codex is ahead overall, 89 to 31. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 90 and 6.
GPT-5.3 Codex has the edge for knowledge tasks in this comparison, averaging 80.3 versus 25.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for coding in this comparison, averaging 87.3 versus 7.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for math in this comparison, averaging 97.7 versus 40.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for reasoning in this comparison, averaging 93.7 versus 35.3. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for agentic tasks in this comparison, averaging 88.1 versus 34. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for multimodal and grounded tasks in this comparison, averaging 91.3 versus 30.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for instruction following in this comparison, averaging 93 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for multilingual tasks in this comparison, averaging 92.8 versus 59.7. Inside this category, MGSM 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.