Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
MiniMax M2.7 finishes one point ahead overall, 57 to 56. 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 K2.5 is also the more expensive model on tokens at $0.50 input / $2.80 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 2.3x on output cost alone. MiniMax M2.7 gives you the larger context window at 200K, compared with 128K for Kimi K2.5.
Pick MiniMax M2.7 if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice if coding is the priority.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Kimi K2.5
82.9
MiniMax M2.7
56.2
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Benchmark data for this category is coming soon.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Benchmark data for this category is coming soon.
Benchmark data for this category is coming soon.
Benchmark data for this category is coming soon.
MiniMax M2.7 is ahead overall, 57 to 56.
Kimi K2.5 has the edge for coding in this comparison, averaging 82.9 versus 56.2. MiniMax M2.7 stays close enough that the answer can still flip depending on your workload.
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