Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.5
64
MiniMax M3
76
Verified leaderboard positions: Kimi K2.5 #15 · MiniMax M3 #12
Pick MiniMax M3 if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice if multimodal & grounded is the priority.
Agentic
+17.3 difference
Coding
+2.8 difference
Multimodal
+13.6 difference
Kimi K2.5
MiniMax M3
$0.6 / $3
$0.3 / $1.2
45 t/s
N/A
2.38s
N/A
256K
1M
Pick MiniMax M3 if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice if multimodal & grounded is the priority.
MiniMax M3 is clearly ahead on the provisional aggregate, 76 to 64. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiniMax M3's sharpest advantage is in agentic, where it averages 71.9 against 54.6. The single biggest benchmark swing on the page is BrowseComp, 60.6% to 83.5%. Kimi K2.5 does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
Kimi K2.5 is also the more expensive model on tokens at $0.60 input / $3.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M3. That is roughly 2.5x on output cost alone. MiniMax M3 gives you the larger context window at 1M, compared with 256K for Kimi K2.5.
MiniMax M3 is ahead on BenchLM's provisional leaderboard, 76 to 64. The biggest single separator in this matchup is BrowseComp, where the scores are 60.6% and 83.5%.
MiniMax M3 has the edge for coding in this comparison, averaging 67 versus 64.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
MiniMax M3 has the edge for agentic tasks in this comparison, averaging 71.9 versus 54.6. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for multimodal and grounded tasks in this comparison, averaging 78.5 versus 64.9. Inside this category, VideoMMMU is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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