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 80. 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 66.2. The single biggest benchmark swing on the page is LiveCodeBench, 80 to 61. GPT-5.1 does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
GPT-5.3-Codex-Spark is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $1.50 input / $6.00 output per 1M tokens for GPT-5.1. GPT-5.3-Codex-Spark gives you the larger context window at 256K, compared with 200K for GPT-5.1.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. GPT-5.1 only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
GPT-5.3-Codex-Spark
85.6
GPT-5.1
75.8
GPT-5.3-Codex-Spark
82.3
GPT-5.1
66.2
GPT-5.3-Codex-Spark
88.3
GPT-5.1
91.8
GPT-5.3-Codex-Spark
92.7
GPT-5.1
88.4
GPT-5.3-Codex-Spark
78.3
GPT-5.1
72.5
GPT-5.3-Codex-Spark
92
GPT-5.1
89
GPT-5.3-Codex-Spark
90.8
GPT-5.1
87.7
GPT-5.3-Codex-Spark
96.7
GPT-5.1
95.4
GPT-5.3-Codex-Spark is ahead overall, 87 to 80. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80 and 61.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 72.5. 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 66.2. 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 95.4. 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 88.4. 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 75.8. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.1 has the edge for multimodal and grounded tasks in this comparison, averaging 91.8 versus 88.3. 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 89. 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 87.7. 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.