Model comparison
Kimi K2.7 Code vs MiniMax M2.7
Head-to-head evidence from 16 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Kimi K2.7 Code #92 (Estimated); MiniMax M2.7 #40 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.7 Code and MiniMax M2.7 share 16 comparable benchmark results. 0 of 8 categories are comparable. 7 results are unique to Kimi K2.7 Code; 19 to MiniMax M2.7.
Updated July 27, 2026- Shared results
- 16
- Kimi K2.7 Code only
- 7
- MiniMax M2.7 only
- 19
- Comparable categories
- 0 / 8
Benchmark data for Kimi K2.7 Code and MiniMax M2.7 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Kimi K2.7 Code is priced at $0.95 input / $4.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. Kimi K2.7 Code has the larger context window at 256K, compared with 200K for MiniMax M2.7.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Kimi K2.7 Code | Δ | MiniMax M2.7 |
|---|---|---|---|
| Agentic | Kimi K2.7 CodeNot measured | MarginNo overlap | MiniMax M2.757.0 |
| Coding | Kimi K2.7 CodeNot measured | MarginNo overlap | MiniMax M2.753.3 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.7 Code | MiniMax M2.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.7 Code$0.95 input / $4 output | MiniMax M2.7$0.3 input / $1.2 output | MiniMax M2.7 has the lower combined listed price. |
| Generation speedtokens per second | Kimi K2.7 CodeNot available | MiniMax M2.745 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.7 CodeNot available | MiniMax M2.72.53 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.7 Code256K | MiniMax M2.7200K | Kimi K2.7 Code lists the larger context window. |
Benchmark Deep Dive
Agentic14 benchmarks
| Benchmark | Kimi K2.7 Code | MiniMax M2.7 | Result |
|---|---|---|---|
| Kimi Claw 24/7Source | 46.9% | — | Not comparable |
| MCP AtlasSource | 76% | — | Not comparable |
| MCP Mark VerifiedSource | 81.1% | — | Not comparable |
| AA Agentic IndexSource | 29.6% | 25.6% | Kimi K2.7 Code leads |
| τ²-bench resultsSource | 90.1% | 84.8% | Kimi K2.7 Code leads |
| GDPval-AASource | 34.3% | 32.9% | Kimi K2.7 Code leads |
| GDPval-AASource | 1186 | 1159 | Kimi K2.7 Code leads |
| Terminal-Bench 2.0Source | — | 57% | Not comparable |
| ToolathlonSource | — | 46.3% | Not comparable |
| MLE-Bench LiteSource | — | 66.6% | Not comparable |
| MM-ClawBenchSource | — | 62.7% | Not comparable |
| Claw-EvalSource | — | 48.7% | Not comparable |
| APEX-Agents-AASource | — | 10.6% | Not comparable |
| Gert LabsSource | — | 40.40% | Not comparable |
Coding15 benchmarks
| Benchmark | Kimi K2.7 Code | MiniMax M2.7 | Result |
|---|---|---|---|
| Kimi Code Bench v2Source | 62.0% | — | Not comparable |
| ProgramBenchSource | 53.6% | — | Not comparable |
| MLS-Bench LiteSource | 35.1% | — | Not comparable |
| cursorBench32Source | 49.7% | — | Not comparable |
| AA Coding IndexSource | 60.8% | 52.6% | Kimi K2.7 Code leads |
| AA-SciCodeSource | 47.5% | 47.0% | Kimi K2.7 Code leads |
| SWE-bench Verified*Source | — | 75.4% | Not comparable |
| SWE-bench ProSource | — | 56.2% | Not comparable |
| SWE-RebenchSource | — | 51.9% | Not comparable |
| SWE MultilingualSource | — | 76.5% | Not comparable |
| Multi-SWE BenchSource | — | 52.7% | Not comparable |
| VIBE-ProSource | — | 55.6% | Not comparable |
| NL2RepoSource | — | 39.8% | Not comparable |
| Vibe Code BenchSource | — | 27.04% | Not comparable |
| React Native EvalsSource | — | 71.4% | Not comparable |
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | Kimi K2.7 Code | MiniMax M2.7 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 42.0% | 38.1% | Kimi K2.7 Code leads |
| AA-GPQA DiamondSource | 89.6% | 87.4% | Kimi K2.7 Code leads |
| AA-HLESource | 32.8% | 28.1% | Kimi K2.7 Code leads |
| AA-Omniscience IndexSource | -10.7% | 0.7% | MiniMax M2.7 leads |
| AA-Omniscience AccuracySource | 38.6% | 26.1% | Kimi K2.7 Code leads |
| AA-Omniscience Hallucination RateSource | 80.3% | 34.4% | MiniMax M2.7 leads |
| GPQA-DSource | — | 87.0% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 80.8% | Not comparable |
Math1 benchmarks
| Benchmark | Kimi K2.7 Code | MiniMax M2.7 | Result |
|---|---|---|---|
| AIME25 (Arcee)Source | — | 80.0% | Not comparable |
Multimodal1 benchmarks
| Benchmark | Kimi K2.7 Code | MiniMax M2.7 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1300 | 1271 | Kimi K2.7 Code leads |
Inst. Following1 benchmarks
| Benchmark | Kimi K2.7 Code | MiniMax M2.7 | Result |
|---|---|---|---|
| AA-IFBenchSource | 63.1% | 75.7% | MiniMax M2.7 leads |
Frequently Asked Questions (3)
Can I compare Kimi K2.7 Code and MiniMax M2.7 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Kimi K2.7 Code and MiniMax M2.7 today?
Kimi K2.7 Code: $0.95 input / $4.00 output per 1M tokens MiniMax M2.7: $0.30 input / $1.20 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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