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 62. 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 40.4. The single biggest benchmark swing on the page is LiveCodeBench, 80 to 36.
GPT-5.3-Codex-Spark is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.50 input / $3.00 output per 1M tokens for Gemini 3 Flash. That is roughly 2.7x on output cost alone. GPT-5.3-Codex-Spark is the reasoning model in the pair, while Gemini 3 Flash 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 3 Flash 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. Gemini 3 Flash only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
GPT-5.3-Codex-Spark
85.6
Gemini 3 Flash
57.5
GPT-5.3-Codex-Spark
82.3
Gemini 3 Flash
40.4
GPT-5.3-Codex-Spark
88.3
Gemini 3 Flash
79.6
GPT-5.3-Codex-Spark
92.7
Gemini 3 Flash
72
GPT-5.3-Codex-Spark
78.3
Gemini 3 Flash
52.9
GPT-5.3-Codex-Spark
92
Gemini 3 Flash
85
GPT-5.3-Codex-Spark
90.8
Gemini 3 Flash
80.5
GPT-5.3-Codex-Spark
96.7
Gemini 3 Flash
74
GPT-5.3-Codex-Spark is ahead overall, 87 to 62. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80 and 36.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 52.9. 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 40.4. 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 74. 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 72. 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 57.5. 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 79.6. 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 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 80.5. Inside this category, MMLU-ProX 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.