Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.5
91
o3-mini
55
Verified leaderboard positions: GPT-5.5 #5 · o3-mini unranked
Pick GPT-5.5 if you want the stronger benchmark profile. o3-mini only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Coding
+9.3 difference
Knowledge
+10.8 difference
GPT-5.5
o3-mini
$5 / $30
$1.1 / $4.4
N/A
160 t/s
N/A
7.12s
1M
200K
Pick GPT-5.5 if you want the stronger benchmark profile. o3-mini only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
GPT-5.5 is clearly ahead on the provisional aggregate, 91 to 55. 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 coding, where it averages 58.6 against 49.3. The single biggest benchmark swing on the page is GPQA, 93.6% to 77.2%. o3-mini does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-5.5 is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $1.10 input / $4.40 output per 1M tokens for o3-mini. That is roughly 6.8x on output cost alone. GPT-5.5 gives you the larger context window at 1M, compared with 200K for o3-mini.
GPT-5.5 is ahead on BenchLM's provisional leaderboard, 91 to 55. The biggest single separator in this matchup is GPQA, where the scores are 93.6% and 77.2%.
o3-mini has the edge for knowledge tasks in this comparison, averaging 77.2 versus 66.4. Inside this category, AA-HLE is the benchmark that creates the most daylight between them.
GPT-5.5 has the edge for coding in this comparison, averaging 58.6 versus 49.3. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
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