Model comparison
Kimi K2.5 vs Qwen3.6-27B
Head-to-head evidence from 34 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Kimi K2.5 #54 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.5 and Qwen3.6-27B share 34 comparable benchmark results. 5 of 8 categories are comparable. 29 results are unique to Kimi K2.5; 20 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 34
- Kimi K2.5 only
- 29
- Qwen3.6-27B only
- 20
- Comparable categories
- 5 / 8
Pick Kimi K2.5 if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 34 shared benchmark results across 7 evidence categories; 5 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Kimi K2.5 is clearly ahead on the BenchAlign aggregate, 59.66 to 53.82. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5's sharpest advantage is in knowledge, where it averages 56.9 against 53.3. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 50.8% to 59.3%. Qwen3.6-27B does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
Kimi K2.5 is also the more expensive model on tokens at $0.60 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B is the reasoning model in the pair, while Kimi K2.5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Qwen3.6-27B gives you the larger context window at 262K, compared with 256K for Kimi K2.5.
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 K2.5 | Δ | Qwen3.6-27B |
|---|---|---|---|
| Math | Kimi K2.560.6 | Margin→ 28.6 | Qwen3.6-27B89.2 |
| Coding | Kimi K2.559.4 | Margin→ 18.1 | Qwen3.6-27B77.5 |
| Agentic | Kimi K2.555.0 | Margin→ 4.3 | Qwen3.6-27B59.3 |
| Knowledge | Kimi K2.556.9 | Margin← 3.6 | Qwen3.6-27B53.3 |
| Multimodal | Kimi K2.578.5 | Margin← 1.8 | Qwen3.6-27B76.7 |
| Reasoning | Kimi K2.561.0 | MarginNo overlap | Qwen3.6-27BNot measured |
| Multilingual | Kimi K2.582.3 | MarginNo overlap | Qwen3.6-27BNot measured |
| Inst. Following | Kimi K2.593.9 | MarginNo overlap | Qwen3.6-27BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 50.8%B 59.3%Winner: Qwen3.6-27BΔ 8.5Terminal-Bench 2.0: Kimi K2.5 scored 50.8%; Qwen3.6-27B scored 59.3%. Qwen3.6-27B wins this benchmark. - Source ↗
HLE
KnowledgeA 30.1%B 24%Winner: Kimi K2.5Δ 6.1HLE: Kimi K2.5 scored 30.1%; Qwen3.6-27B scored 24%. Kimi K2.5 wins this benchmark. - Source ↗
SuperGPQA
KnowledgeA 69.2%B 66%Winner: Kimi K2.5Δ 3.2SuperGPQA: Kimi K2.5 scored 69.2%; Qwen3.6-27B scored 66%. Kimi K2.5 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 50.7%B 53.5%Winner: Qwen3.6-27BΔ 2.8SWE-bench Pro: Kimi K2.5 scored 50.7%; Qwen3.6-27B scored 53.5%. Qwen3.6-27B wins this benchmark. - Source ↗
HMMT Feb 2026
MathA 87.1%B 84.3%Winner: Kimi K2.5Δ 2.8HMMT Feb 2026: Kimi K2.5 scored 87.1%; Qwen3.6-27B scored 84.3%. Kimi K2.5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.5 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.5$0.6 input / $3 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | Kimi K2.545 tok/s | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.52.38 s | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.5256K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
AgenticQwen3.6-27B wins21 benchmarks
| Benchmark | Kimi K2.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 50.8% | 59.3% | Qwen3.6-27B leads |
| BrowseCompSource | 60.6% | — | Not comparable |
| Claw-EvalSource | 52.3% | 72.4% | Qwen3.6-27B leads |
| QwenClawBenchSource | 54.3% | 53.4% | Kimi K2.5 leads |
| τ³-bench resultsSource | 65.7% | — | Not comparable |
| DeepSearchQASource | 77.1% | — | Not comparable |
| DeepPlanningSource | 14.4% | — | Not comparable |
| ToolathlonSource | 27.8% | — | Not comparable |
| MCP AtlasSource | 29.5% | — | Not comparable |
| MCP-TasksSource | 59.1% | — | Not comparable |
| WideResearchSource | 72.7% | — | Not comparable |
| τ²-bench resultsSource | 95.9% | 94.2% | Kimi K2.5 leads |
| APEX-Agents-AASource | 11.5% | — | Not comparable |
| Gert LabsSource | 45.88% | 54.84% | Qwen3.6-27B leads |
| ResearchClawBenchSource | 14.0% | — | Not comparable |
| JobBenchSource | 8.7% | — | Not comparable |
| AA Agentic IndexSource | 21.7% | 27.0% | Qwen3.6-27B leads |
| GDPval-AASource | 25.4% | 32.0% | Qwen3.6-27B leads |
| GDPval-AASource | 1009 | 1140 | Qwen3.6-27B leads |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
CodingQwen3.6-27B wins13 benchmarks
| Benchmark | Kimi K2.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 76.8% | 77.2% | Qwen3.6-27B leads |
| SWE-bench Verified*Source | 70.8% | — | Not comparable |
| LiveCodeBench v6Source | 85.0% | — | Not comparable |
| SWE-bench ProSource | 50.7% | 53.5% | Qwen3.6-27B leads |
| SWE MultilingualSource | 73% | 71.3% | Kimi K2.5 leads |
| SWE-RebenchSource | 58.5% | — | Not comparable |
| React Native EvalsSource | 77.2% | — | Not comparable |
| SciCodeSource | 48.7% | — | Not comparable |
| AA-SciCodeSource | 49.0% | 39.8% | Kimi K2.5 leads |
| AA Coding IndexSource | 46.8% | 53.7% | Qwen3.6-27B leads |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
Reasoning3 benchmarks
KnowledgeKimi K2.5 wins14 benchmarks
| Benchmark | Kimi K2.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| GPQASource | 87.6% | 87.8% | Qwen3.6-27B leads |
| GPQA-DSource | 87.6% | — | Not comparable |
| SuperGPQASource | 69.2% | 66% | Kimi K2.5 leads |
| MMLU-ProSource | 87.1% | 86.2% | Kimi K2.5 leads |
| MMLU-Pro (Arcee)Source | 87.1% | — | Not comparable |
| HLESource | 30.1% | 24% | Kimi K2.5 leads |
| Artificial Analysis Intelligence IndexSource | 35.4% | 37.0% | Qwen3.6-27B leads |
| AA-GPQA DiamondSource | 87.9% | 84.2% | Kimi K2.5 leads |
| AA-HLESource | 29.4% | 21.6% | Kimi K2.5 leads |
| AA-Omniscience IndexSource | -8.1% | -19.8% | Kimi K2.5 leads |
| AA-Omniscience AccuracySource | 34.3% | 19.2% | Kimi K2.5 leads |
| AA-Omniscience Hallucination RateSource | 64.6% | 48.3% | Qwen3.6-27B leads |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
MathQwen3.6-27B wins9 benchmarks
| Benchmark | Kimi K2.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| AIME 2025Source | 96.1% | — | Not comparable |
| AIME26Source | 95.8% | 94.1% | Kimi K2.5 leads |
| AIME25 (Arcee)Source | 96.3% | — | Not comparable |
| HMMT Feb 2025Source | 95.4% | 93.8% | Kimi K2.5 leads |
| HMMT Nov 2025Source | 91.1% | 90.7% | Kimi K2.5 leads |
| HMMT Feb 2026Source | 87.1% | 84.3% | Kimi K2.5 leads |
| MMAnswerBenchSource | 81.8% | 80.8% | Kimi K2.5 leads |
| FrontierMath v2 (Tiers 1-3)Source | 27.900% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 4.200% | — | Not comparable |
Multilingual2 benchmarks
MultimodalKimi K2.5 wins19 benchmarks
| Benchmark | Kimi K2.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| MMMU-ProSource | 78.5% | 75.8% | Kimi K2.5 leads |
| Video-MMESource | 87.4% | — | Not comparable |
| MMVUSource | 80.4% | — | Not comparable |
| VideoMMMUSource | 86.6% | 84.4% | Kimi K2.5 leads |
| AA-MMMU-ProSource | 75.4% | 74.6% | Kimi K2.5 leads |
| Design Arena WebsiteSource | 1279 | — | Not comparable |
| MMMUSource | — | 82.9% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CharXivSource | — | 78.4% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| ERQASource | — | 62.5% | Not comparable |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
Frequently Asked Questions (6)
Which is better, Kimi K2.5 or Qwen3.6-27B?
Kimi K2.5 is ahead on BenchLM's BenchAlign leaderboard, 59.66 to 53.82. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 50.8% and 59.3%.
Which is better for knowledge tasks, Kimi K2.5 or Qwen3.6-27B?
Kimi K2.5 has the edge for knowledge tasks in this comparison, averaging 56.9 versus 53.3. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, Kimi K2.5 or Qwen3.6-27B?
Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 versus 59.4. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, Kimi K2.5 or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 60.6. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Kimi K2.5 or Qwen3.6-27B?
Qwen3.6-27B has the edge for agentic tasks in this comparison, averaging 59.3 versus 55. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Kimi K2.5 or Qwen3.6-27B?
Kimi K2.5 has the edge for multimodal and grounded tasks in this comparison, averaging 78.5 versus 76.7. Inside this category, MMMU-Pro 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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