Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.6
85
MiniMax M3
76
Verified leaderboard positions: Kimi K2.6 #9 · MiniMax M3 #12
Pick Kimi K2.6 if you want the stronger benchmark profile. MiniMax M3 only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Agentic
+1.2 difference
Coding
+5.0 difference
Multimodal
+14.8 difference
Kimi K2.6
MiniMax M3
$0.95 / $4
$0.3 / $1.2
N/A
N/A
N/A
N/A
256K
1M
Pick Kimi K2.6 if you want the stronger benchmark profile. MiniMax M3 only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Kimi K2.6 is clearly ahead on the provisional aggregate, 85 to 76. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.6's sharpest advantage is in multimodal & grounded, where it averages 79.7 against 64.9. The single biggest benchmark swing on the page is OSWorld-Verified, 73.1% to 70.1%.
Kimi K2.6 is also the more expensive model on tokens at $0.95 input / $4.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M3. That is roughly 3.3x on output cost alone. Kimi K2.6 is the reasoning model in the pair, while MiniMax M3 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. MiniMax M3 gives you the larger context window at 1M, compared with 256K for Kimi K2.6.
Kimi K2.6 is ahead on BenchLM's provisional leaderboard, 85 to 76. The biggest single separator in this matchup is OSWorld-Verified, where the scores are 73.1% and 70.1%.
Kimi K2.6 has the edge for coding in this comparison, averaging 72 versus 67. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Kimi K2.6 has the edge for agentic tasks in this comparison, averaging 73.1 versus 71.9. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
Kimi K2.6 has the edge for multimodal and grounded tasks in this comparison, averaging 79.7 versus 64.9. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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