Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 nano
27
Qwen3 235B 2507
34
Pick Qwen3 235B 2507 if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you need the larger 1M context window.
Knowledge
+25.9 difference
GPT-4.1 nano
Qwen3 235B 2507
$0.1 / $0.4
$0 / $0
181 t/s
N/A
0.63s
N/A
1M
128K
Pick Qwen3 235B 2507 if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you need the larger 1M context window.
Qwen3 235B 2507 is clearly ahead on the provisional aggregate, 34 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3 235B 2507's sharpest advantage is in knowledge, where it averages 76.2 against 50.3. The single biggest benchmark swing on the page is GPQA, 50.3% to 77.5%.
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 Qwen3 235B 2507. That is roughly Infinityx on output cost alone. GPT-4.1 nano gives you the larger context window at 1M, compared with 128K for Qwen3 235B 2507.
Qwen3 235B 2507 is ahead on BenchLM's provisional leaderboard, 34 to 27. The biggest single separator in this matchup is GPQA, where the scores are 50.3% and 77.5%.
Qwen3 235B 2507 has the edge for knowledge tasks in this comparison, averaging 76.2 versus 50.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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