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 52. 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 18.5. The single biggest benchmark swing on the page is SWE-bench Verified, 80 to 5.
GPT-5.3-Codex-Spark is the reasoning model in the pair, while Gemini 1.5 Pro is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Gemini 1.5 Pro 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 1.5 Pro only becomes the better choice if you need the larger 2M context window or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.3-Codex-Spark
85.6
Gemini 1.5 Pro
49.8
GPT-5.3-Codex-Spark
82.3
Gemini 1.5 Pro
18.5
GPT-5.3-Codex-Spark
88.3
Gemini 1.5 Pro
74.1
GPT-5.3-Codex-Spark
92.7
Gemini 1.5 Pro
66.9
GPT-5.3-Codex-Spark
78.3
Gemini 1.5 Pro
44.2
GPT-5.3-Codex-Spark
92
Gemini 1.5 Pro
77
GPT-5.3-Codex-Spark
90.8
Gemini 1.5 Pro
69.5
GPT-5.3-Codex-Spark
96.7
Gemini 1.5 Pro
67.5
GPT-5.3-Codex-Spark is ahead overall, 87 to 52. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 80 and 5.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 44.2. 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 18.5. 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 67.5. 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 66.9. 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 49.8. 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 74.1. Inside this category, OfficeQA 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 77. 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 69.5. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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