Model comparison
Kimi K2.6 vs Mistral Medium 3.5 128B
Head-to-head evidence from 18 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Kimi K2.6 #61 (Estimated); Mistral Medium 3.5 128B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.6 and Mistral Medium 3.5 128B share 18 comparable benchmark results. 1 of 8 categories are comparable. 32 results are unique to Kimi K2.6; 7 to Mistral Medium 3.5 128B.
Updated July 27, 2026- Shared results
- 18
- Kimi K2.6 only
- 32
- Mistral Medium 3.5 128B only
- 7
- Comparable categories
- 1 / 8
Treat this as a split decision. Kimi K2.6 makes more sense if you want the cheaper token bill; Mistral Medium 3.5 128B is the better fit if coding is the priority.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Kimi K2.6 and Mistral Medium 3.5 128B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Mistral Medium 3.5 128B is also the more expensive model on tokens at $1.50 input / $7.50 output per 1M tokens, versus $0.95 input / $4.00 output per 1M tokens for Kimi K2.6.
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 K2.6 | Δ | Mistral Medium 3.5 128B |
|---|---|---|---|
| Coding | Kimi K2.664.4 | Margin→ 13.2 | Mistral Medium 3.5 128B77.6 |
| Agentic | Kimi K2.673.5 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Knowledge | Kimi K2.642.2 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Math | Kimi K2.667.1 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Multimodal | Kimi K2.679.8 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 80.2%B 77.6%Winner: Kimi K2.6Δ 2.6SWE-bench Verified: Kimi K2.6 scored 80.2%; Mistral Medium 3.5 128B scored 77.6%. Kimi K2.6 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.6 | Mistral Medium 3.5 128B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.6$0.95 input / $4 output | Mistral Medium 3.5 128B$1.5 input / $7.5 output | Kimi K2.6 has the lower combined listed price. |
| Generation speedtokens per second | Kimi K2.6Not available | Mistral Medium 3.5 128BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.6Not available | Mistral Medium 3.5 128BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.6256K | Mistral Medium 3.5 128B256K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic22 benchmarks
| Benchmark | Kimi K2.6 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 66.7% | — | Not comparable |
| BrowseCompSource | 83.2% | — | Not comparable |
| OSWorld-VerifiedSource | 73.1% | — | Not comparable |
| ToolathlonSource | 50% | — | Not comparable |
| MCP AtlasSource | 55.9% | — | Not comparable |
| Claw-EvalSource | 62.3% | — | Not comparable |
| DeepSearchQASource | 92.5% | — | Not comparable |
| WideResearchSource | 80.8% | — | Not comparable |
| AA Agentic IndexSource | 30.3% | 19.0% | Kimi K2.6 leads |
| τ²-bench resultsSource | 95.9% | 94.2% | Kimi K2.6 leads |
| GDPval-AASource | 34.4% | 21.6% | Kimi K2.6 leads |
| GDPval-AASource | 1188 | 933 | Kimi K2.6 leads |
| APEX-Agents-AASource | 28.5% | — | Not comparable |
| Gert LabsSource | 56.82% | 39.10% | Kimi K2.6 leads |
| ResearchClawBenchSource | 18.0% | — | Not comparable |
| OSWorld 2.0Source | 4.6% | — | Not comparable |
| τ³-bench resultsSource | — | 91.4% | Not comparable |
| AA EnterpriseOps-GymSource | — | 33.7% | Not comparable |
| AA Harvey LABSource | — | 69.1% | Not comparable |
| terminalBenchHardSource | — | 33.3% | Not comparable |
| AA BriefcaseSource | — | 516 | Not comparable |
| AA Tau3 BankingSource | — | 14.4% | Not comparable |
CodingMistral Medium 3.5 128B wins10 benchmarks
| Benchmark | Kimi K2.6 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.2% | 77.6% | Kimi K2.6 leads |
| LiveCodeBench v6Source | 89.6% | — | Not comparable |
| SWE-bench ProSource | 58.6% | — | Not comparable |
| SWE MultilingualSource | 76.7% | — | Not comparable |
| SciCodeSource | 52.2% | — | Not comparable |
| Terminal-Bench 2.0Source | 66.7% | — | Not comparable |
| Vibe Code BenchSource | 37.89% | — | Not comparable |
| cursorBench31Source | 47.6% | — | Not comparable |
| AA Coding IndexSource | 61.8% | 46.9% | Kimi K2.6 leads |
| AA-SciCodeSource | 53.5% | 39.6% | Kimi K2.6 leads |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | Kimi K2.6 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| GPQASource | 90.5% | — | Not comparable |
| GPQA-DSource | 90.5% | — | Not comparable |
| HLESource | 34.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 44.2% | 29.9% | Kimi K2.6 leads |
| AA-GPQA DiamondSource | 91.1% | 74.8% | Kimi K2.6 leads |
| AA-HLESource | 35.9% | 12.8% | Kimi K2.6 leads |
| AA-Omniscience IndexSource | 6.4% | -36.3% | Kimi K2.6 leads |
| AA-Omniscience AccuracySource | 32.8% | 25.1% | Kimi K2.6 leads |
| AA-Omniscience Hallucination RateSource | 39.3% | 82.0% | Kimi K2.6 leads |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Math5 benchmarks
Multimodal7 benchmarks
| Benchmark | Kimi K2.6 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| MMMU-ProSource | 79.4% | — | Not comparable |
| MMMU-Pro w/ PythonSource | 80.1% | — | Not comparable |
| CharXivSource | 80.4% | — | Not comparable |
| MathVisionSource | 87.4% | — | Not comparable |
| V*Source | 96.9% | — | Not comparable |
| AA-MMMU-ProSource | 79.4% | 64.9% | Kimi K2.6 leads |
| Design Arena WebsiteSource | 1302 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Kimi K2.6 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-IFBenchSource | 76.0% | 68.8% | Kimi K2.6 leads |
Frequently Asked Questions (2)
Which is better, Kimi K2.6 or Mistral Medium 3.5 128B?
Kimi K2.6 and Mistral Medium 3.5 128B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for coding, Kimi K2.6 or Mistral Medium 3.5 128B?
Mistral Medium 3.5 128B has the edge for coding in this comparison, averaging 77.6 versus 64.4. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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