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 48. 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 28.1. The single biggest benchmark swing on the page is LiveCodeBench, 80 to 25.
GPT-5.3-Codex-Spark is the reasoning model in the pair, while GPT-OSS 120B 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-5.3-Codex-Spark gives you the larger context window at 256K, compared with 128K for GPT-OSS 120B.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. GPT-OSS 120B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.3-Codex-Spark
85.6
GPT-OSS 120B
44.8
GPT-5.3-Codex-Spark
82.3
GPT-OSS 120B
28.1
GPT-5.3-Codex-Spark
88.3
GPT-OSS 120B
48.8
GPT-5.3-Codex-Spark
92.7
GPT-OSS 120B
55.2
GPT-5.3-Codex-Spark
78.3
GPT-OSS 120B
41.5
GPT-5.3-Codex-Spark
92
GPT-OSS 120B
79
GPT-5.3-Codex-Spark
90.8
GPT-OSS 120B
70.7
GPT-5.3-Codex-Spark
96.7
GPT-OSS 120B
59.5
GPT-5.3-Codex-Spark is ahead overall, 87 to 48. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80 and 25.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 41.5. Inside this category, MMLU 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 28.1. Inside this category, LiveCodeBench 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 59.5. 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 55.2. 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 44.8. 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 48.8. 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 79. 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 70.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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