Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 finishes one point ahead overall, 88 to 87. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
GPT-5.2's sharpest advantage is in multimodal & grounded, where it averages 95 against 88.3. The single biggest benchmark swing on the page is MMMU-Pro, 95 to 86. GPT-5.3-Codex-Spark does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.2 gives you the larger context window at 400K, compared with 256K for GPT-5.3-Codex-Spark.
Pick GPT-5.2 if you want the stronger benchmark profile. GPT-5.3-Codex-Spark only becomes the better choice if coding is the priority.
GPT-5.2
85.4
GPT-5.3-Codex-Spark
85.6
GPT-5.2
81.8
GPT-5.3-Codex-Spark
82.3
GPT-5.2
95
GPT-5.3-Codex-Spark
88.3
GPT-5.2
93.2
GPT-5.3-Codex-Spark
92.7
GPT-5.2
79.5
GPT-5.3-Codex-Spark
78.3
GPT-5.2
94
GPT-5.3-Codex-Spark
92
GPT-5.2
92.4
GPT-5.3-Codex-Spark
90.8
GPT-5.2
97.2
GPT-5.3-Codex-Spark
96.7
GPT-5.2 is ahead overall, 88 to 87. The biggest single separator in this matchup is MMMU-Pro, where the scores are 95 and 86.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 79.5 versus 78.3. Inside this category, FrontierScience 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 81.8. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for math in this comparison, averaging 97.2 versus 96.7. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for reasoning in this comparison, averaging 93.2 versus 92.7. 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 85.4. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 95 versus 88.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for instruction following in this comparison, averaging 94 versus 92. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for multilingual tasks in this comparison, averaging 92.4 versus 90.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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