Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.5
91
Step 3.7 Flash
72
Verified leaderboard positions: GPT-5.5 #5 · Step 3.7 Flash unranked
Pick GPT-5.5 if you want the stronger benchmark profile. Step 3.7 Flash only becomes the better choice if you want the cheaper token bill.
Agentic
+15.6 difference
Coding
+2.3 difference
GPT-5.5
Step 3.7 Flash
$5 / $30
$0.2 / $1.15
N/A
N/A
N/A
N/A
1M
256K
Pick GPT-5.5 if you want the stronger benchmark profile. Step 3.7 Flash only becomes the better choice if you want the cheaper token bill.
GPT-5.5 is clearly ahead on the provisional aggregate, 91 to 72. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.5's sharpest advantage is in agentic, where it averages 81.5 against 65.9. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 82% to 59.5%.
GPT-5.5 is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $0.20 input / $1.15 output per 1M tokens for Step 3.7 Flash. That is roughly 26.1x on output cost alone. GPT-5.5 gives you the larger context window at 1M, compared with 256K for Step 3.7 Flash.
GPT-5.5 is ahead on BenchLM's provisional leaderboard, 91 to 72. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 82% and 59.5%.
GPT-5.5 has the edge for coding in this comparison, averaging 58.6 versus 56.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.5 has the edge for agentic tasks in this comparison, averaging 81.5 versus 65.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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