Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.3 Instant is clearly ahead on the aggregate, 87 to 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3 Instant's sharpest advantage is in coding, where it averages 78.7 against 40.6. The single biggest benchmark swing on the page is SWE-bench Pro, 83 to 43.
GPT-5.3 Instant is the reasoning model in the pair, while Llama 3.1 405B 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 Instant if you want the stronger benchmark profile. Llama 3.1 405B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.3 Instant
82.9
Llama 3.1 405B
53.9
GPT-5.3 Instant
78.7
Llama 3.1 405B
40.6
GPT-5.3 Instant
95
Llama 3.1 405B
62.3
GPT-5.3 Instant
94.2
Llama 3.1 405B
68.3
GPT-5.3 Instant
80.8
Llama 3.1 405B
53.2
GPT-5.3 Instant
96
Llama 3.1 405B
86
GPT-5.3 Instant
93.4
Llama 3.1 405B
80.1
GPT-5.3 Instant
97.2
Llama 3.1 405B
74.9
GPT-5.3 Instant is ahead overall, 87 to 59. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 83 and 43.
GPT-5.3 Instant has the edge for knowledge tasks in this comparison, averaging 80.8 versus 53.2. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.3 Instant has the edge for coding in this comparison, averaging 78.7 versus 40.6. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.3 Instant has the edge for math in this comparison, averaging 97.2 versus 74.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5.3 Instant has the edge for reasoning in this comparison, averaging 94.2 versus 68.3. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-5.3 Instant has the edge for agentic tasks in this comparison, averaging 82.9 versus 53.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.3 Instant has the edge for multimodal and grounded tasks in this comparison, averaging 95 versus 62.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.3 Instant has the edge for instruction following in this comparison, averaging 96 versus 86. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.3 Instant has the edge for multilingual tasks in this comparison, averaging 93.4 versus 80.1. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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