MiniMax-M2.7vsKimi K2.5
Across 8 shared benchmarks, MiniMax-M2.7 leads overall: MiniMax-M2.7 wins 7, Kimi K2.5 wins 1, with 0 ties and an average score difference of +6.44.
MiniMax-M2.7
MiniMaxAI · 2026-03-18 · Reasoning model
Kimi K2.5
Moonshot AI · 2026-01-27 · Multimodal model
MiniMax-M2.77 wins(88%)(13%)1 winKimi K2.5
Benchmark scores
Grouped by capability, sorted by largest gap within each. 8 shared benchmarks.
Claw-style Agent Evaluation
MiniMax-M2.7 3/3| Benchmark | MiniMax-M2.7 | Kimi K2.5 | Diff |
|---|---|---|---|
| PinchBench v2 | 66.7530 / 45Reported best (effort unspecified) | 54.6036 / 45Reported best (effort unspecified) | +12.15 |
| Claw Bench | 91.705 / 29Thinking (With Tools) | 81.7018 / 29Thinking (With Tools) | +10 |
| Pinch Bench | 87.1010 / 38Thinking (With Tools) | 84.8018 / 38Thinking (With Tools) | +2.30 |
AI Agent - Tool Usage
MiniMax-M2.7 2/2| Benchmark | MiniMax-M2.7 | Kimi K2.5 | Diff |
|---|---|---|---|
| Terminal-Bench 2.1 | 55.40121 / 192Thinking (With Tools) | 45.70137 / 192Thinking (With Tools) | +9.70 |
| Terminal Bench 2.0 | 5725 / 48Thinking (With Tools) | 50.8035 / 48Thinking (With Tools) | +6.20 |
Agent Level Benchmark
Kimi K2.5 1/1| Benchmark | MiniMax-M2.7 | Kimi K2.5 | Diff |
|---|---|---|---|
| τ³-Banking | 9.90129 / 164Thinking (With Tools) | 14.20113 / 164Thinking (With Tools) | -4.30 |
Coding and Software Engineer
MiniMax-M2.7 1/1| Benchmark | MiniMax-M2.7 | Kimi K2.5 | Diff |
|---|---|---|---|
| SWE-Bench Pro - Public | 56.2029 / 62Thinking (With Tools) | 50.7047 / 62Thinking (With Tools) | +5.50 |
Productivity Knowledge
MiniMax-M2.7 1/1| Benchmark | MiniMax-M2.7 | Kimi K2.5 | Diff |
|---|---|---|---|
| GDPval-AA | 507 / 15Thinking (No Tools) | 409 / 15Thinking (No Tools) | +10 |
Specs
| Field | MiniMax-M2.7 | Kimi K2.5 |
|---|---|---|
| Publisher | MiniMaxAI | Moonshot AI |
| Release date | 2026-03-18 | 2026-01-27 |
| Model type | Reasoning model | Multimodal model |
| Architecture | MoE | MoE |
| Parameters | 229B | 1T |
| Context length | 200K | 256K |
| Max output | 200K | 16K |
API pricing
Prices use DataLearner records when available; missing fields are not inferred.
| Item | MiniMax-M2.7 | Kimi K2.5 |
|---|---|---|
| Text input | $0.3 / 1M tokens | $0.6 / 1M tokens |
| Text output | $1.2 / 1M tokens | $3 / 1M tokens |
| Cache read | $0.06 / 1M tokens | $0.1 / 1M tokens |
| Cache write | $0.375 / 1M tokens | Not public |
Summary
- MiniMax-M2.7leads in:Claw-style Agent Evaluation (3/3), AI Agent - Tool Usage (2/2), Coding and Software Engineer (1/1), Productivity Knowledge (1/1)
- Kimi K2.5leads in:Agent Level Benchmark (1/1)
On average across the 8 shared benchmarks, MiniMax-M2.7 scores 6.44 higher.
Largest single-benchmark gap: PinchBench v2 — MiniMax-M2.7 66.75 vs Kimi K2.5 54.60 (+12.15).
Page generated from structured model, pricing and benchmark records. No real-time LLM is used to write the prose.