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 38. 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 18. The single biggest benchmark swing on the page is SWE-bench Pro, 83 to 19.
GPT-5.3 Instant is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.03 input / $0.12 output per 1M tokens for LFM2-24B-A2B. That is roughly 116.7x on output cost alone. GPT-5.3 Instant is the reasoning model in the pair, while LFM2-24B-A2B 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. GPT-5.3 Instant gives you the larger context window at 128K, compared with 32K for LFM2-24B-A2B.
Pick GPT-5.3 Instant if you want the stronger benchmark profile. LFM2-24B-A2B 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 Instant
82.9
LFM2-24B-A2B
33.4
GPT-5.3 Instant
78.7
LFM2-24B-A2B
18
GPT-5.3 Instant
95
LFM2-24B-A2B
41.7
GPT-5.3 Instant
94.2
LFM2-24B-A2B
46.6
GPT-5.3 Instant
80.8
LFM2-24B-A2B
35.6
GPT-5.3 Instant
96
LFM2-24B-A2B
68
GPT-5.3 Instant
93.4
LFM2-24B-A2B
61.4
GPT-5.3 Instant
97.2
LFM2-24B-A2B
50.4
GPT-5.3 Instant is ahead overall, 87 to 38. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 83 and 19.
GPT-5.3 Instant has the edge for knowledge tasks in this comparison, averaging 80.8 versus 35.6. Inside this category, MMLU 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 18. 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 50.4. 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 46.6. Inside this category, SimpleQA 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 33.4. 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 41.7. 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 68. 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 61.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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