Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 nano
27
Hy3 Preview
62
Pick Hy3 Preview if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if instruction following is the priority or you need the larger 1M context window.
Knowledge
+3.6 difference
Inst. Following
+20.1 difference
GPT-4.1 nano
Hy3 Preview
$0.1 / $0.4
$0 / $0
181 t/s
N/A
0.63s
N/A
1M
256K
Pick Hy3 Preview if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if instruction following is the priority or you need the larger 1M context window.
Hy3 Preview is clearly ahead on the provisional aggregate, 62 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1 nano is also the more expensive model on tokens at $0.10 input / $0.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Hy3 Preview. That is roughly Infinityx on output cost alone. Hy3 Preview is the reasoning model in the pair, while GPT-4.1 nano 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-4.1 nano gives you the larger context window at 1M, compared with 256K for Hy3 Preview.
Hy3 Preview is ahead on BenchLM's provisional leaderboard, 62 to 27. The biggest single separator in this matchup is GPQA, where the scores are 50.3% and 87.2%.
GPT-4.1 nano has the edge for knowledge tasks in this comparison, averaging 50.3 versus 46.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-4.1 nano has the edge for instruction following in this comparison, averaging 83.2 versus 63.1. Hy3 Preview stays close enough that the answer can still flip depending on your workload.
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