Model comparison
Kimi K2.7 Code vs Mistral Small 4
Head-to-head evidence from 15 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Kimi K2.7 Code #92 (Estimated); Mistral Small 4 #147 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.7 Code and Mistral Small 4 share 15 comparable benchmark results. 0 of 8 categories are comparable. 8 results are unique to Kimi K2.7 Code; 1 to Mistral Small 4.
Updated July 27, 2026- Shared results
- 15
- Kimi K2.7 Code only
- 8
- Mistral Small 4 only
- 1
- Comparable categories
- 0 / 8
Benchmark data for Kimi K2.7 Code and Mistral Small 4 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 5 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 $0.15 input / $0.60 output per 1M tokens for Mistral Small 4.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.7 Code | Mistral Small 4 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.7 Code$0.95 input / $4 output | Mistral Small 4$0.15 input / $0.6 output | Mistral Small 4 has the lower combined listed price. |
| Generation speedtokens per second | Kimi K2.7 CodeNot available | Mistral Small 4175 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.7 CodeNot available | Mistral Small 40.64 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.7 Code256K | Mistral Small 4256K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic7 benchmarks
| Benchmark | Kimi K2.7 Code | Mistral Small 4 | 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% | 4.7% | Kimi K2.7 Code leads |
| τ²-bench resultsSource | 90.1% | 41.2% | Kimi K2.7 Code leads |
| GDPval-AASource | 34.3% | 4.6% | Kimi K2.7 Code leads |
| GDPval-AASource | 1186 | 592 | Kimi K2.7 Code leads |
Coding6 benchmarks
| Benchmark | Kimi K2.7 Code | Mistral Small 4 | 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% | 26.6% | Kimi K2.7 Code leads |
| AA-SciCodeSource | 47.5% | 38.0% | Kimi K2.7 Code leads |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Kimi K2.7 Code | Mistral Small 4 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 42.0% | 19.6% | Kimi K2.7 Code leads |
| AA-GPQA DiamondSource | 89.6% | 76.9% | Kimi K2.7 Code leads |
| AA-HLESource | 32.8% | 9.5% | Kimi K2.7 Code leads |
| AA-Omniscience IndexSource | -10.7% | -29.9% | Kimi K2.7 Code leads |
| AA-Omniscience AccuracySource | 38.6% | 22.1% | Kimi K2.7 Code leads |
| AA-Omniscience Hallucination RateSource | 80.3% | 66.8% | Mistral Small 4 leads |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Kimi K2.7 Code | Mistral Small 4 | Result |
|---|---|---|---|
| AA-IFBenchSource | 63.1% | 48.2% | Kimi K2.7 Code leads |
Frequently Asked Questions (3)
Can I compare Kimi K2.7 Code and Mistral Small 4 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 Mistral Small 4 today?
Kimi K2.7 Code: $0.95 input / $4.00 output per 1M tokens Mistral Small 4: $0.15 input / $0.60 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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