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 70. 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 49.1. The single biggest benchmark swing on the page is LiveCodeBench, 80 to 40.
o3 is also the more expensive model on tokens at $10.00 input / $40.00 output per 1M tokens, versus $2.00 input / $8.00 output per 1M tokens for GPT-5.3-Codex-Spark. That is roughly 5.0x on output cost alone. GPT-5.3-Codex-Spark gives you the larger context window at 256K, compared with 200K for o3.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. o3 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GPT-5.3-Codex-Spark
85.6
o3
69.9
GPT-5.3-Codex-Spark
82.3
o3
49.1
GPT-5.3-Codex-Spark
88.3
o3
72.3
GPT-5.3-Codex-Spark
92.7
o3
82.6
GPT-5.3-Codex-Spark
78.3
o3
66
GPT-5.3-Codex-Spark
92
o3
85
GPT-5.3-Codex-Spark
90.8
o3
81.1
GPT-5.3-Codex-Spark
96.7
o3
87.5
GPT-5.3-Codex-Spark is ahead overall, 87 to 70. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80 and 40.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 66. 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 49.1. 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 87.5. 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 82.6. Inside this category, BBH 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 69.9. 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 72.3. 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 85. 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 81.1. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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