Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude 3.5 Sonnet
41
GPT-4.1 nano
27
Pick Claude 3.5 Sonnet if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Knowledge
+9.1 difference
Claude 3.5 Sonnet
GPT-4.1 nano
$3 / $15
$0.1 / $0.4
N/A
181 t/s
N/A
0.63s
200K
1M
Pick Claude 3.5 Sonnet if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Claude 3.5 Sonnet is clearly ahead on the provisional aggregate, 41 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude 3.5 Sonnet's sharpest advantage is in knowledge, where it averages 59.4 against 50.3. The single biggest benchmark swing on the page is GPQA, 59.4% to 50.3%.
Claude 3.5 Sonnet is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 37.5x on output cost alone. GPT-4.1 nano gives you the larger context window at 1M, compared with 200K for Claude 3.5 Sonnet.
Claude 3.5 Sonnet is ahead on BenchLM's provisional leaderboard, 41 to 27. The biggest single separator in this matchup is GPQA, where the scores are 59.4% and 50.3%.
Claude 3.5 Sonnet has the edge for knowledge tasks in this comparison, averaging 59.4 versus 50.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
For engineers, researchers, and the plain curious — a weekly brief on new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.