Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.5 Pro
100
Kimi 2.6
83
Verified leaderboard positions: GPT-5.5 Pro unranked · Kimi 2.6 #4
Pick GPT-5.5 Pro if you want the stronger benchmark profile. Kimi 2.6 only becomes the better choice if you want the cheaper token bill.
Agentic
+17.0 difference
Knowledge
+3.4 difference
GPT-5.5 Pro
Kimi 2.6
$30 / $180
$0.95 / $4
N/A
N/A
N/A
N/A
1M
256K
Pick GPT-5.5 Pro if you want the stronger benchmark profile. Kimi 2.6 only becomes the better choice if you want the cheaper token bill.
GPT-5.5 Pro is clearly ahead on the provisional aggregate, 100 to 83. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.5 Pro's sharpest advantage is in agentic, where it averages 90.1 against 73.1. The single biggest benchmark swing on the page is HLE, 57.2% to 34.7%.
GPT-5.5 Pro is also the more expensive model on tokens at $30.00 input / $180.00 output per 1M tokens, versus $0.95 input / $4.00 output per 1M tokens for Kimi 2.6. That is roughly 45.0x on output cost alone. GPT-5.5 Pro gives you the larger context window at 1M, compared with 256K for Kimi 2.6.
GPT-5.5 Pro is ahead on BenchLM's provisional leaderboard, 100 to 83. The biggest single separator in this matchup is HLE, where the scores are 57.2% and 34.7%.
GPT-5.5 Pro has the edge for knowledge tasks in this comparison, averaging 57.2 versus 53.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.5 Pro has the edge for agentic tasks in this comparison, averaging 90.1 versus 73.1. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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