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 63. 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 41.4. The single biggest benchmark swing on the page is LiveCodeBench, 80 to 37.
GPT-5.3-Codex-Spark is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.25 input / $2.00 output per 1M tokens for Seed-2.0-Lite. That is roughly 4.0x on output cost alone. GPT-5.3-Codex-Spark is the reasoning model in the pair, while Seed-2.0-Lite 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.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. Seed-2.0-Lite only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.3-Codex-Spark
85.6
Seed-2.0-Lite
55.1
GPT-5.3-Codex-Spark
82.3
Seed-2.0-Lite
41.4
GPT-5.3-Codex-Spark
88.3
Seed-2.0-Lite
79.6
GPT-5.3-Codex-Spark
92.7
Seed-2.0-Lite
73
GPT-5.3-Codex-Spark
78.3
Seed-2.0-Lite
53.9
GPT-5.3-Codex-Spark
92
Seed-2.0-Lite
89
GPT-5.3-Codex-Spark
90.8
Seed-2.0-Lite
82.5
GPT-5.3-Codex-Spark
96.7
Seed-2.0-Lite
75
GPT-5.3-Codex-Spark is ahead overall, 87 to 63. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80 and 37.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 53.9. 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 41.4. 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 75. 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 73. 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 55.1. 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 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 82.5. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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