Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi 2.6
83
MiMo-V2.5-Pro
82
Verified leaderboard positions: Kimi 2.6 #5 · MiMo-V2.5-Pro unranked
Pick Kimi 2.6 if you want the stronger benchmark profile. MiMo-V2.5-Pro only becomes the better choice if you need the larger 1M context window.
Agentic
+4.7 difference
Coding
+14.8 difference
Knowledge
+5.8 difference
Kimi 2.6
MiMo-V2.5-Pro
$0 / $0
$1 / $3
N/A
N/A
N/A
N/A
256K
1M
Pick Kimi 2.6 if you want the stronger benchmark profile. MiMo-V2.5-Pro only becomes the better choice if you need the larger 1M context window.
Kimi 2.6 finishes one point ahead on BenchLM's provisional leaderboard, 83 to 82. 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.
Kimi 2.6's sharpest advantage is in coding, where it averages 72 against 57.2. The single biggest benchmark swing on the page is HLE, 34.7% to 48%.
MiMo-V2.5-Pro is also the more expensive model on tokens at $1.00 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Kimi 2.6. That is roughly Infinityx on output cost alone. MiMo-V2.5-Pro gives you the larger context window at 1M, compared with 256K for Kimi 2.6.
Kimi 2.6 is ahead on BenchLM's provisional leaderboard, 83 to 82. The biggest single separator in this matchup is HLE, where the scores are 34.7% and 48%.
Kimi 2.6 has the edge for knowledge tasks in this comparison, averaging 53.8 versus 48. Inside this category, HLE is the benchmark that creates the most daylight between them.
Kimi 2.6 has the edge for coding in this comparison, averaging 72 versus 57.2. Inside this category, terminalBench2 is the benchmark that creates the most daylight between them.
Kimi 2.6 has the edge for agentic tasks in this comparison, averaging 73.1 versus 68.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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