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 66. 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 47.3. The single biggest benchmark swing on the page is LiveCodeBench, 80 to 44.
GPT-5.3-Codex-Spark gives you the larger context window at 256K, compared with 128K for DeepSeekMath V2.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. DeepSeekMath V2 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GPT-5.3-Codex-Spark
85.6
DeepSeekMath V2
63.9
GPT-5.3-Codex-Spark
82.3
DeepSeekMath V2
47.3
GPT-5.3-Codex-Spark
88.3
DeepSeekMath V2
68.1
GPT-5.3-Codex-Spark
92.7
DeepSeekMath V2
75.9
GPT-5.3-Codex-Spark
78.3
DeepSeekMath V2
61
GPT-5.3-Codex-Spark
92
DeepSeekMath V2
83
GPT-5.3-Codex-Spark
90.8
DeepSeekMath V2
82.5
GPT-5.3-Codex-Spark
96.7
DeepSeekMath V2
84
GPT-5.3-Codex-Spark is ahead overall, 87 to 66. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80 and 44.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 61. 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 47.3. 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 84. 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 75.9. Inside this category, MRCRv2 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 63.9. 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 68.1. Inside this category, MMMU-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 82.5. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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