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 64. 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 42.9. The single biggest benchmark swing on the page is LiveCodeBench, 80 to 36.
GPT-5.3-Codex-Spark is the reasoning model in the pair, while Claude 4 Sonnet 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 4 Sonnet.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. Claude 4 Sonnet 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 4 Sonnet
57.9
GPT-5.3-Codex-Spark
82.3
Claude 4 Sonnet
42.9
GPT-5.3-Codex-Spark
88.3
Claude 4 Sonnet
79.7
GPT-5.3-Codex-Spark
92.7
Claude 4 Sonnet
71.8
GPT-5.3-Codex-Spark
78.3
Claude 4 Sonnet
56.8
GPT-5.3-Codex-Spark
92
Claude 4 Sonnet
83
GPT-5.3-Codex-Spark
90.8
Claude 4 Sonnet
82.1
GPT-5.3-Codex-Spark
96.7
Claude 4 Sonnet
76.1
GPT-5.3-Codex-Spark is ahead overall, 87 to 64. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80 and 36.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 56.8. 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 42.9. Inside this category, LiveCodeBench 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 76.1. 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 71.8. 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 57.9. 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 79.7. 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 83. 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 82.1. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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