Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.5 (Reasoning)
76
MiniMax M3
76
Verified leaderboard positions: Kimi K2.5 (Reasoning) unranked · MiniMax M3 #12
Treat this as a split decision. Kimi K2.5 (Reasoning) makes more sense if multimodal & grounded is the priority or you want the stronger reasoning-first profile; MiniMax M3 is the better fit if agentic is the priority or you want the cheaper token bill.
Agentic
+17.3 difference
Coding
+9.8 difference
Multimodal
+13.6 difference
Kimi K2.5 (Reasoning)
MiniMax M3
$0.6 / $3
$0.3 / $1.2
N/A
N/A
N/A
N/A
128K
1M
Treat this as a split decision. Kimi K2.5 (Reasoning) makes more sense if multimodal & grounded is the priority or you want the stronger reasoning-first profile; MiniMax M3 is the better fit if agentic is the priority or you want the cheaper token bill.
Kimi K2.5 (Reasoning) and MiniMax M3 finish on the same provisional overall score, so this is less about a single winner and more about where the edge shows up. The provisional headline says tie; the benchmark table is where the real choice happens.
Kimi K2.5 (Reasoning) 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. Kimi K2.5 (Reasoning) 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 128K for Kimi K2.5 (Reasoning).
Kimi K2.5 (Reasoning) and MiniMax M3 are tied on the provisional overall score, so the right pick depends on which category matters most for your use case.
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 67. Inside this category, SWE-bench Verified 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, BrowseComp is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for multimodal and grounded tasks in this comparison, averaging 78.5 versus 64.9. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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