Model comparison
Kimi K2 (Jul 2025) vs Qwen3.5 27B
Kimi K2 (Jul 2025) and Qwen3.5 27B score almost the same on the Noometry Index (40.9 vs 41.4), so choose on price, context window or the category you care about most.
Last verified . 20 shared benchmarks.
Alibaba (Qwen)Summary
- They share 20 benchmarks with published results for both. Kimi K2 (Jul 2025) scores higher in 3 categories and Qwen3.5 27B in 5 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where Kimi K2 (Jul 2025) leads 43.1 to 38.6.
- The biggest single-benchmark swing is Vectara Hallucination Rate: 17.9% for Kimi K2 (Jul 2025) and 12.1% for Qwen3.5 27B.
- Qwen3.5 27B is cheaper at $0.30 / $2.40 per million input/output tokens, against $0.57 / $2.30 for Kimi K2 (Jul 2025).
Side by side
| Kimi K2 (Jul 2025) | Qwen3.5 27B | |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 40.9 | 41.4 |
| Released | 2025-07-12 | 2026-02-23 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 262K | 66K |
| Input $ / M tokens | $0.57 | $0.30 |
| Output $ / M tokens | $2.30 | $2.40 |
| Results tracked | 42 | 28 |
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Category by category
Coding Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 43.1 (#83), Qwen3.5 27B: 38.6 (#159)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5 27B |
|---|---|---|
| WeirdML | 42.8% | 39.5% |
| LMArena Coding | 1399 | 1427 |
| ALE-Bench | 597.5 | 349.45 |
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| LMArena WebDev | — | 1357 |
| GSO | 4.9% | — |
Agentic & Tool Use Not comparable
Kimi K2 (Jul 2025): 32.2 (#59), Qwen3.5 27B: —
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5 27B |
|---|---|---|
| Terminal-Bench | 35.7% | — |
| Berkeley Function Calling Leaderboard | 59.1% | — |
| METR Time Horizons | 59.2% | — |
| Vending-Bench 2 | — | 201.98 |
Reasoning Qwen3.5 27B leads
Kimi K2 (Jul 2025): 22.7 (#173), Qwen3.5 27B: 26.6 (#116)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Hard Prompts | 1384 | 1414 |
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| NYT Connections (extended) | — | 47.9% |
| Thematic Generalization | — | 45.5% |
| DTBench | — | 82.4% |
| LMCA | — | 34% |
| Epoch Capabilities Index | 146.02 | — |
| ForecastBench | 60.2 | — |
Math Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 40.1 (#81), Qwen3.5 27B: 36.8 (#103)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Math | 1396 | 1428 |
| MathArena Final-Answer Competitions | — | 56.7% |
| Omni-MATH | 65.4% | — |
| FrontierMath (Feb 2025 set) | 21.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Too close to call
Kimi K2 (Jul 2025): 36.9 (#153), Qwen3.5 27B: 37.4 (#149)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5 27B |
|---|---|---|
| Vectara Hallucination Rate | 17.9% | 12.1% |
| LMArena Expert | 1363 | 1428 |
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| GPQA (HELM) | 65.3% | — |
Multimodal Not comparable
Kimi K2 (Jul 2025): —, Qwen3.5 27B: 38.7 (#56)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Vision | — | 1240 |
Multilingual Qwen3.5 27B leads
Kimi K2 (Jul 2025): 49.8 (#125), Qwen3.5 27B: 51.0 (#112)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Non-English | 1372 | 1390 |
| LMArena Chinese | 1416 | 1478 |
| LMArena French | 1379 | 1409 |
| LMArena German | 1386 | 1393 |
| LMArena Japanese | 1349 | 1345 |
| LMArena Korean | 1324 | 1359 |
| LMArena Russian | 1384 | 1389 |
| LMArena Spanish | 1383 | 1408 |
Instruction Following Qwen3.5 27B leads
Kimi K2 (Jul 2025): 71.3 (#151), Qwen3.5 27B: 73.7 (#114)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Instruction Following | 1347 | 1393 |
| IFEval | 85% | — |
Long Context Qwen3.5 27B leads
Kimi K2 (Jul 2025): 41.2 (#140), Qwen3.5 27B: 43.1 (#103)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Longer Query | 1353 | 1413 |
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |
Writing & Preference Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 62.5 (#76), Qwen3.5 27B: 59.5 (#106)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Text | 1380 | 1409 |
| LMArena Creative Writing | 1349 | 1362 |
| LMArena Multi-Turn | 1371 | 1410 |
| Short-Story Creative Writing | 85.6% | — |
| EQ-Bench Creative Writing | 1666 | — |
| WildBench | 86.2% | — |
Frequently asked questions
Is Kimi K2 (Jul 2025) better than Qwen3.5 27B?
Kimi K2 (Jul 2025) and Qwen3.5 27B score almost the same on the Noometry Index (40.9 vs 41.4), so choose on price, context window or the category you care about most.
Which is cheaper, Kimi K2 (Jul 2025) or Qwen3.5 27B?
Qwen3.5 27B is cheaper. It lists at $0.30 per million input tokens and $2.40 per million output tokens; Kimi K2 (Jul 2025) lists at $0.57 and $2.30.
Is Kimi K2 (Jul 2025) or Qwen3.5 27B better for coding?
Kimi K2 (Jul 2025) scores higher on coding benchmarks: 43.1 versus 38.6 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Kimi K2 (Jul 2025) and Qwen3.5 27B share?
20 benchmarks have published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and Qwen3.5 27B has 28.