Model comparison
Kimi K2.6 vs MiniMax-M2.7
Kimi K2.6 is the stronger model overall, scoring 47.7 to 37.7 on the Noometry Index. MiniMax-M2.7 costs 3.3× less per token, which makes it the better buy when Kimi K2.6's lead doesn't matter for your workload.
Last verified . 28 shared benchmarks.
MiniMaxSummary
- They share 28 benchmarks with published results for both. Kimi K2.6 scores higher in 8 categories and MiniMax-M2.7 in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.6 leads 57.0 to 25.9.
- The biggest single-benchmark swing is NYT Connections (extended): 87.2% for Kimi K2.6 and 24.7% for MiniMax-M2.7.
- MiniMax-M2.7 is cheaper at $0.30 / $1.20 per million input/output tokens, against $0.95 / $4 for Kimi K2.6.
- Kimi K2.6 accepts more context: 262K tokens versus 205K.
Side by side
| Kimi K2.6 | MiniMax-M2.7 | |
|---|---|---|
| Provider | Moonshot AI | MiniMax |
| Noometry Index | 47.7 | 37.7 |
| Released | 2026-04-20 | 2026-03-18 |
| Weights | Open | Open |
| Context window | 262K | 205K |
| Max output | 262K | 131K |
| Input $ / M tokens | $0.95 | $0.30 |
| Output $ / M tokens | $4 | $1.20 |
| Results tracked | 51 | 30 |
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Category by category
Coding Kimi K2.6 leads
Kimi K2.6: 50.7 (#43), MiniMax-M2.7: 41.8 (#120)
| Benchmark | Kimi K2.6 | MiniMax-M2.7 |
|---|---|---|
| LMArena WebDev | 1509 | 1398 |
| SciCode | 53.5% | 47% |
| WeirdML | 55.9% | 37% |
| LMArena Coding | 1488 | 1454 |
| ALE-Bench | 1,093 | 599.25 |
| SWE-bench Verified | 76.7% | — |
Agentic & Tool Use MiniMax-M2.7 leads
Kimi K2.6: 21.9 (#137), MiniMax-M2.7: 25.1 (#111)
| Benchmark | Kimi K2.6 | MiniMax-M2.7 |
|---|---|---|
| ExploitBench | 18.4% | 13.3% |
| GBAEval | 0.9% | 0% |
| Terminal-Bench | — | 45.1% |
| OSWorld 2.0 | 4.6% | — |
| GDP.pdf | 12% | — |
| Vending-Bench 2 | 6,205 | — |
Reasoning Kimi K2.6 leads
Kimi K2.6: 40.5 (#55), MiniMax-M2.7: 19.7 (#253)
| Benchmark | Kimi K2.6 | MiniMax-M2.7 |
|---|---|---|
| NYT Connections (extended) | 87.2% | 24.7% |
| CritPt | 8% | 0.6% |
| LMArena Hard Prompts | 1470 | 1422 |
| Epoch Capabilities Index | 151.05 | 145.85 |
| Chess Puzzles | 26% | — |
| Thematic Generalization | — | 39.3% |
| EBR-Bench | 2.4% | — |
| Mystery Game Puzzles | 18% | — |
| DTBench | 90.9% | — |
| LMCA | 37.3% | — |
Math Kimi K2.6 leads
Kimi K2.6: 57.0 (#41), MiniMax-M2.7: 25.9 (#263)
| Benchmark | Kimi K2.6 | MiniMax-M2.7 |
|---|---|---|
| ProofBench | 16% | 3% |
| LMArena Math | 1475 | 1420 |
| FrontierMath (Tiers 1-3) | 57.2% | — |
| FrontierMath Tier 4 | 25.6% | — |
| MathArena Final-Answer Competitions | 72.9% | — |
| OTIS Mock AIME 2024-2025 | 96.1% | — |
| FrontierMath (Feb 2025 set) | 39% | — |
| FrontierMath Tier 4 (v1) | 14.6% | — |
Knowledge Kimi K2.6 leads
Kimi K2.6: 54.0 (#54), MiniMax-M2.7: 37.7 (#152)
| Benchmark | Kimi K2.6 | MiniMax-M2.7 |
|---|---|---|
| Vectara Hallucination Rate | 10.8% | 12.9% |
| LMArena Expert | 1491 | 1444 |
| GPQA Diamond | 90.8% | — |
| SimpleQA Verified | 34.9% | — |
Multimodal Not comparable
Kimi K2.6: 31.6 (#103), MiniMax-M2.7: —
| Benchmark | Kimi K2.6 | MiniMax-M2.7 |
|---|---|---|
| LMArena Vision | 1283 | — |
| Blueprint-Bench 2 | 3.9% | — |
| Furniture Assembly | 21.7% | — |
| LMArena Document | 1451 | — |
Multilingual Kimi K2.6 leads
Kimi K2.6: 54.9 (#37), MiniMax-M2.7: 50.3 (#123)
| Benchmark | Kimi K2.6 | MiniMax-M2.7 |
|---|---|---|
| LMArena Non-English | 1446 | 1382 |
| LMArena Chinese | 1521 | 1441 |
| LMArena French | 1471 | 1421 |
| LMArena German | 1450 | 1398 |
| LMArena Japanese | 1443 | 1262 |
| LMArena Korean | 1427 | 1313 |
| LMArena Russian | 1446 | 1383 |
| LMArena Spanish | 1464 | 1403 |
Instruction Following Kimi K2.6 leads
Kimi K2.6: 76.3 (#43), MiniMax-M2.7: 74.1 (#103)
| Benchmark | Kimi K2.6 | MiniMax-M2.7 |
|---|---|---|
| LMArena Instruction Following | 1451 | 1405 |
Long Context Kimi K2.6 leads
Kimi K2.6: 44.9 (#52), MiniMax-M2.7: 43.3 (#99)
| Benchmark | Kimi K2.6 | MiniMax-M2.7 |
|---|---|---|
| LMArena Longer Query | 1468 | 1419 |
Writing & Preference Kimi K2.6 leads
Kimi K2.6: 68.5 (#26), MiniMax-M2.7: 58.9 (#112)
| Benchmark | Kimi K2.6 | MiniMax-M2.7 |
|---|---|---|
| LMArena Text | 1455 | 1405 |
| LMArena Creative Writing | 1434 | 1354 |
| LMArena Multi-Turn | 1453 | 1412 |
| EQ-Bench Creative Writing | 1725 | — |
| EQ-Bench 4 | 1202 | — |
Frequently asked questions
Is Kimi K2.6 better than MiniMax-M2.7?
Kimi K2.6 is the stronger model overall, scoring 47.7 to 37.7 on the Noometry Index. MiniMax-M2.7 costs 3.3× less per token, which makes it the better buy when Kimi K2.6's lead doesn't matter for your workload.
Which is cheaper, Kimi K2.6 or MiniMax-M2.7?
MiniMax-M2.7 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; Kimi K2.6 lists at $0.95 and $4.
Is Kimi K2.6 or MiniMax-M2.7 better for coding?
Kimi K2.6 scores higher on coding benchmarks: 50.7 versus 41.8 in the Noometry coding category.
Which has the bigger context window?
Kimi K2.6 does, with 262K tokens against 205K.
How many benchmarks do Kimi K2.6 and MiniMax-M2.7 share?
28 benchmarks have published results for both models. Kimi K2.6 has 51 scored results on Noometry and MiniMax-M2.7 has 30.