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 65. 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 mathematics, where it averages 96.7 against 26.4. The single biggest benchmark swing on the page is AIME 2024, 98 to 26.4.
GPT-5.3-Codex-Spark is the reasoning model in the pair, while GPT-4.1 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. GPT-4.1 gives you the larger context window at 1M, compared with 256K for GPT-5.3-Codex-Spark.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. GPT-4.1 only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.3-Codex-Spark
85.6
GPT-4.1
64.7
GPT-5.3-Codex-Spark
82.3
GPT-4.1
51.7
GPT-5.3-Codex-Spark
88.3
GPT-4.1
73.6
GPT-5.3-Codex-Spark
92.7
GPT-4.1
80.9
GPT-5.3-Codex-Spark
78.3
GPT-4.1
63.3
GPT-5.3-Codex-Spark
92
GPT-4.1
87.4
GPT-5.3-Codex-Spark
90.8
GPT-4.1
69
GPT-5.3-Codex-Spark
96.7
GPT-4.1
26.4
GPT-5.3-Codex-Spark is ahead overall, 87 to 65. The biggest single separator in this matchup is AIME 2024, where the scores are 98 and 26.4.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 63.3. Inside this category, GPQA 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 51.7. Inside this category, SWE-bench Pro 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 26.4. Inside this category, AIME 2024 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 80.9. Inside this category, LongBench v2 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 64.7. 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 73.6. 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 87.4. 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. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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