Model comparison
Kimi K2.6 vs Qwen3.5-9B
Kimi K2.6 is the stronger model overall, scoring 47.7 to 33.8 on the Noometry Index. Qwen3.5-9B costs 15× less per token, which makes it the better buy when Kimi K2.6's lead doesn't matter for your workload.
Last verified . 9 shared benchmarks.
Alibaba (Qwen)Summary
- They share 9 benchmarks with published results for both. Kimi K2.6 scores higher in 5 categories and Qwen3.5-9B in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.6 leads 57.0 to 34.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 96.1% for Kimi K2.6 and 61.7% for Qwen3.5-9B.
- Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.95 / $4 for Kimi K2.6.
Side by side
| Kimi K2.6 | Qwen3.5-9B | |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 47.7 | 33.8 |
| Released | 2026-04-20 | 2026-02-23 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 262K | 66K |
| Input $ / M tokens | $0.95 | $0.10 |
| Output $ / M tokens | $4 | $0.15 |
| Results tracked | 51 | 10 |
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Category by category
Coding Kimi K2.6 leads
Kimi K2.6: 50.7 (#43), Qwen3.5-9B: 35.9 (#217)
| Benchmark | Kimi K2.6 | Qwen3.5-9B |
|---|---|---|
| SciCode | 53.5% | 27.5% |
| SWE-bench Verified | 76.7% | — |
| LMArena WebDev | 1509 | — |
| WeirdML | 55.9% | — |
| LMArena Coding | 1488 | — |
| ALE-Bench | 1,093 | — |
Agentic & Tool Use Kimi K2.6 leads
Kimi K2.6: 21.9 (#137), Qwen3.5-9B: 14.5 (#151)
| Benchmark | Kimi K2.6 | Qwen3.5-9B |
|---|---|---|
| Terminal-Bench | — | 9.2% |
| OSWorld 2.0 | 4.6% | — |
| ExploitBench | 18.4% | — |
| GBAEval | 0.9% | — |
| GDP.pdf | 12% | — |
| Vending-Bench 2 | 6,205 | — |
Reasoning Kimi K2.6 leads
Kimi K2.6: 40.5 (#55), Qwen3.5-9B: 23.1 (#182)
| Benchmark | Kimi K2.6 | Qwen3.5-9B |
|---|---|---|
| CritPt | 8% | 0.3% |
| Chess Puzzles | 26% | 12% |
| DTBench | 90.9% | 71.2% |
| LMCA | 37.3% | 24.5% |
| Epoch Capabilities Index | 151.05 | 139.46 |
| NYT Connections (extended) | 87.2% | — |
| EBR-Bench | 2.4% | — |
| LMArena Hard Prompts | 1470 | — |
| Mystery Game Puzzles | 18% | — |
Math Kimi K2.6 leads
Kimi K2.6: 57.0 (#41), Qwen3.5-9B: 34.8 (#192)
| Benchmark | Kimi K2.6 | Qwen3.5-9B |
|---|---|---|
| MathArena Final-Answer Competitions | 72.9% | 48.5% |
| OTIS Mock AIME 2024-2025 | 96.1% | 61.7% |
| FrontierMath (Tiers 1-3) | 57.2% | — |
| FrontierMath Tier 4 | 25.6% | — |
| ProofBench | 16% | — |
| LMArena Math | 1475 | — |
| FrontierMath (Feb 2025 set) | 39% | — |
| FrontierMath Tier 4 (v1) | 14.6% | — |
Knowledge Kimi K2.6 leads
Kimi K2.6: 54.0 (#54), Qwen3.5-9B: 46.0 (#84)
| Benchmark | Kimi K2.6 | Qwen3.5-9B |
|---|---|---|
| GPQA Diamond | 90.8% | 79% |
| SimpleQA Verified | 34.9% | — |
| Vectara Hallucination Rate | 10.8% | — |
| LMArena Expert | 1491 | — |
Multimodal Not comparable
Kimi K2.6: 31.6 (#103), Qwen3.5-9B: —
| Benchmark | Kimi K2.6 | Qwen3.5-9B |
|---|---|---|
| LMArena Vision | 1283 | — |
| Blueprint-Bench 2 | 3.9% | — |
| Furniture Assembly | 21.7% | — |
| LMArena Document | 1451 | — |
Multilingual Not comparable
Kimi K2.6: 54.9 (#37), Qwen3.5-9B: —
| Benchmark | Kimi K2.6 | Qwen3.5-9B |
|---|---|---|
| LMArena Non-English | 1446 | — |
| LMArena Chinese | 1521 | — |
| LMArena French | 1471 | — |
| LMArena German | 1450 | — |
| LMArena Japanese | 1443 | — |
| LMArena Korean | 1427 | — |
| LMArena Russian | 1446 | — |
| LMArena Spanish | 1464 | — |
Instruction Following Not comparable
Kimi K2.6: 76.3 (#43), Qwen3.5-9B: —
| Benchmark | Kimi K2.6 | Qwen3.5-9B |
|---|---|---|
| LMArena Instruction Following | 1451 | — |
Long Context Not comparable
Kimi K2.6: 44.9 (#52), Qwen3.5-9B: —
| Benchmark | Kimi K2.6 | Qwen3.5-9B |
|---|---|---|
| LMArena Longer Query | 1468 | — |
Writing & Preference Not comparable
Kimi K2.6: 68.5 (#26), Qwen3.5-9B: —
| Benchmark | Kimi K2.6 | Qwen3.5-9B |
|---|---|---|
| LMArena Text | 1455 | — |
| LMArena Creative Writing | 1434 | — |
| EQ-Bench Creative Writing | 1725 | — |
| EQ-Bench 4 | 1202 | — |
| LMArena Multi-Turn | 1453 | — |
Frequently asked questions
Is Kimi K2.6 better than Qwen3.5-9B?
Kimi K2.6 is the stronger model overall, scoring 47.7 to 33.8 on the Noometry Index. Qwen3.5-9B costs 15× less per token, which makes it the better buy when Kimi K2.6's lead doesn't matter for your workload.
Which is cheaper, Kimi K2.6 or Qwen3.5-9B?
Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; Kimi K2.6 lists at $0.95 and $4.
Is Kimi K2.6 or Qwen3.5-9B better for coding?
Kimi K2.6 scores higher on coding benchmarks: 50.7 versus 35.9 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Kimi K2.6 and Qwen3.5-9B share?
9 benchmarks have published results for both models. Kimi K2.6 has 51 scored results on Noometry and Qwen3.5-9B has 10.