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 71. 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 49.2. The single biggest benchmark swing on the page is LiveCodeBench, 80 to 44.
GPT-5.3-Codex-Spark gives you the larger context window at 256K, compared with 200K for o3-pro.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. o3-pro only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GPT-5.3-Codex-Spark
85.6
o3-pro
70.4
GPT-5.3-Codex-Spark
82.3
o3-pro
49.2
GPT-5.3-Codex-Spark
88.3
o3-pro
74.1
GPT-5.3-Codex-Spark
92.7
o3-pro
83.6
GPT-5.3-Codex-Spark
78.3
o3-pro
67.1
GPT-5.3-Codex-Spark
92
o3-pro
82
GPT-5.3-Codex-Spark
90.8
o3-pro
81.1
GPT-5.3-Codex-Spark
96.7
o3-pro
89
GPT-5.3-Codex-Spark is ahead overall, 87 to 71. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80 and 44.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 67.1. 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 49.2. 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 89. Inside this category, MATH-500 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 83.6. 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 70.4. 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, 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 82. 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.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.