Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Pro has the cleaner overall profile here, landing at 90 versus 87. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-5.2 Pro's sharpest advantage is in multimodal & grounded, where it averages 96 against 88.3. The single biggest benchmark swing on the page is MMMU-Pro, 96 to 86.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 output per 1M tokens, versus $2.00 input / $8.00 output per 1M tokens for GPT-5.3-Codex-Spark. That is roughly 18.8x on output cost alone. GPT-5.2 Pro gives you the larger context window at 400K, compared with 256K for GPT-5.3-Codex-Spark.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. GPT-5.3-Codex-Spark only becomes the better choice if you want the cheaper token bill.
GPT-5.2 Pro
85.9
GPT-5.3-Codex-Spark
85.6
GPT-5.2 Pro
84.8
GPT-5.3-Codex-Spark
82.3
GPT-5.2 Pro
96
GPT-5.3-Codex-Spark
88.3
GPT-5.2 Pro
95.2
GPT-5.3-Codex-Spark
92.7
GPT-5.2 Pro
81.5
GPT-5.3-Codex-Spark
78.3
GPT-5.2 Pro
95
GPT-5.3-Codex-Spark
92
GPT-5.2 Pro
93.4
GPT-5.3-Codex-Spark
90.8
GPT-5.2 Pro
98.2
GPT-5.3-Codex-Spark
96.7
GPT-5.2 Pro is ahead overall, 90 to 87. The biggest single separator in this matchup is MMMU-Pro, where the scores are 96 and 86.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 78.3. Inside this category, FrontierScience is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for coding in this comparison, averaging 84.8 versus 82.3. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for math in this comparison, averaging 98.2 versus 96.7. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for reasoning in this comparison, averaging 95.2 versus 92.7. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for agentic tasks in this comparison, averaging 85.9 versus 85.6. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 96 versus 88.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for instruction following in this comparison, averaging 95 versus 92. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multilingual tasks in this comparison, averaging 93.4 versus 90.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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