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 70. 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 51.2. The single biggest benchmark swing on the page is LiveCodeBench, 80 to 45.
GPT-5.3-Codex-Spark gives you the larger context window at 256K, compared with 128K for DeepSeek V3.2 (Thinking).
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. DeepSeek V3.2 (Thinking) only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GPT-5.3-Codex-Spark
85.6
DeepSeek V3.2 (Thinking)
69.4
GPT-5.3-Codex-Spark
82.3
DeepSeek V3.2 (Thinking)
51.2
GPT-5.3-Codex-Spark
88.3
DeepSeek V3.2 (Thinking)
71
GPT-5.3-Codex-Spark
92.7
DeepSeek V3.2 (Thinking)
80.6
GPT-5.3-Codex-Spark
78.3
DeepSeek V3.2 (Thinking)
64.4
GPT-5.3-Codex-Spark
92
DeepSeek V3.2 (Thinking)
85
GPT-5.3-Codex-Spark
90.8
DeepSeek V3.2 (Thinking)
80.8
GPT-5.3-Codex-Spark
96.7
DeepSeek V3.2 (Thinking)
85.1
GPT-5.3-Codex-Spark is ahead overall, 87 to 70. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80 and 45.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 64.4. 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 51.2. 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 85.1. Inside this category, MATH-500 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 80.6. 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 69.4. 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 71. 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 85. 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 80.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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