Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 2.5 Pro
65
Kimi K2.5
64
Verified leaderboard positions: Gemini 2.5 Pro unranked · Kimi K2.5 #11
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Coding
+0.4 difference
Knowledge
+24.3 difference
Gemini 2.5 Pro
Kimi K2.5
$1.25 / $10
$0.6 / $3
117 t/s
45 t/s
21.19s
2.38s
1M
256K
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Gemini 2.5 Pro finishes one point ahead on BenchLM's provisional leaderboard, 65 to 64. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Gemini 2.5 Pro is also the more expensive model on tokens at $1.25 input / $10.00 output per 1M tokens, versus $0.60 input / $3.00 output per 1M tokens for Kimi K2.5. That is roughly 3.3x on output cost alone. Gemini 2.5 Pro gives you the larger context window at 1M, compared with 256K for Kimi K2.5.
Gemini 2.5 Pro is ahead on BenchLM's provisional leaderboard, 65 to 64. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 63.8% and 76.8%.
Kimi K2.5 has the edge for knowledge tasks in this comparison, averaging 65.1 versus 40.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for coding in this comparison, averaging 64.2 versus 63.8. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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