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 81. 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 60.3. The single biggest benchmark swing on the page is SWE-bench Verified, 80 to 58. Gemini 3 Pro Deep Think does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
Gemini 3 Pro Deep Think gives you the larger context window at 2M, compared with 256K for GPT-5.3-Codex-Spark.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. Gemini 3 Pro Deep Think only becomes the better choice if multimodal & grounded is the priority or you need the larger 2M context window.
GPT-5.3-Codex-Spark
85.6
Gemini 3 Pro Deep Think
78.1
GPT-5.3-Codex-Spark
82.3
Gemini 3 Pro Deep Think
60.3
GPT-5.3-Codex-Spark
88.3
Gemini 3 Pro Deep Think
95
GPT-5.3-Codex-Spark
92.7
Gemini 3 Pro Deep Think
94.5
GPT-5.3-Codex-Spark
78.3
Gemini 3 Pro Deep Think
74.7
GPT-5.3-Codex-Spark
92
Gemini 3 Pro Deep Think
89
GPT-5.3-Codex-Spark
90.8
Gemini 3 Pro Deep Think
87.4
GPT-5.3-Codex-Spark
96.7
Gemini 3 Pro Deep Think
94.5
GPT-5.3-Codex-Spark is ahead overall, 87 to 81. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 80 and 58.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 74.7. 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 60.3. Inside this category, SWE-bench Verified 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 94.5. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
Gemini 3 Pro Deep Think has the edge for reasoning in this comparison, averaging 94.5 versus 92.7. 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 78.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Gemini 3 Pro Deep Think 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-5.3-Codex-Spark has the edge for instruction following in this comparison, averaging 92 versus 89. 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 87.4. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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