Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 nano
60
Step 3.7 Flash
72
Pick Step 3.7 Flash if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you need the larger 400K context window.
Agentic
+23.0 difference
GPT-5.4 nano
Step 3.7 Flash
$0.2 / $1.25
$0.2 / $1.15
191 t/s
N/A
3.64s
N/A
400K
256K
Pick Step 3.7 Flash if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you need the larger 400K context window.
Step 3.7 Flash is clearly ahead on the provisional aggregate, 72 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Step 3.7 Flash's sharpest advantage is in agentic, where it averages 65.9 against 42.9. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 46.3% to 59.5%.
GPT-5.4 nano is also the more expensive model on tokens at $0.20 input / $1.25 output per 1M tokens, versus $0.20 input / $1.15 output per 1M tokens for Step 3.7 Flash. GPT-5.4 nano gives you the larger context window at 400K, compared with 256K for Step 3.7 Flash.
Step 3.7 Flash is ahead on BenchLM's provisional leaderboard, 72 to 60. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 46.3% and 59.5%.
Step 3.7 Flash has the edge for agentic tasks in this comparison, averaging 65.9 versus 42.9. Inside this category, Toolathlon is the benchmark that creates the most daylight between them.
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