Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.3-Codex-Spark is clearly ahead on the aggregate, 87 to 51. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3-Codex-Spark's sharpest advantage is in coding, where it averages 82.3 against 19. The single biggest benchmark swing on the page is SWE-bench Verified, 80 to 10.
GPT-5.3-Codex-Spark is the reasoning model in the pair, while Claude 3 Opus 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-Spark gives you the larger context window at 256K, compared with 200K for Claude 3 Opus.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. Claude 3 Opus only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.3-Codex-Spark
85.6
Claude 3 Opus
48.1
GPT-5.3-Codex-Spark
82.3
Claude 3 Opus
19
GPT-5.3-Codex-Spark
88.3
Claude 3 Opus
70.3
GPT-5.3-Codex-Spark
92.7
Claude 3 Opus
61.6
GPT-5.3-Codex-Spark
78.3
Claude 3 Opus
45
GPT-5.3-Codex-Spark
92
Claude 3 Opus
77
GPT-5.3-Codex-Spark
90.8
Claude 3 Opus
69.8
GPT-5.3-Codex-Spark
96.7
Claude 3 Opus
65.9
GPT-5.3-Codex-Spark is ahead overall, 87 to 51. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 80 and 10.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 45. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for coding in this comparison, averaging 82.3 versus 19. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for math in this comparison, averaging 96.7 versus 65.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for reasoning in this comparison, averaging 92.7 versus 61.6. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for agentic tasks in this comparison, averaging 85.6 versus 48.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for multimodal and grounded tasks in this comparison, averaging 88.3 versus 70.3. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for instruction following in this comparison, averaging 92 versus 77. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for multilingual tasks in this comparison, averaging 90.8 versus 69.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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