Model comparison
Kimi K2 (Jul 2025) vs Qwen3.5-9B
Kimi K2 (Jul 2025) is the stronger model overall, scoring 40.9 to 33.3 on the Noometry Index. Qwen3.5-9B costs 8.9× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. Kimi K2 (Jul 2025) scores higher in 4 categories and Qwen3.5-9B in 1 category; 4 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Kimi K2 (Jul 2025) leads 32.2 to 14.4.
- The biggest single-benchmark swing is Terminal-Bench: 35.7% for Kimi K2 (Jul 2025) and 9.2% for Qwen3.5-9B.
- Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.57 / $2.30 for Kimi K2 (Jul 2025).
Side by side
| Kimi K2 (Jul 2025) | Qwen3.5-9B | |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 40.9 | 33.3 |
| Released | 2025-07-12 | 2026-02-23 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 262K | 66K |
| Input $ / M tokens | $0.57 | $0.10 |
| Output $ / M tokens | $2.30 | $0.15 |
| Results tracked | 42 | 10 |
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Category by category
Coding Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 43.1 (#83), Qwen3.5-9B: 35.3 (#213)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-9B |
|---|---|---|
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| SciCode | — | 27.5% |
| GSO | 4.9% | — |
| WeirdML | 42.8% | — |
| LMArena Coding | 1399 | — |
| ALE-Bench | 597.5 | — |
Agentic & Tool Use Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 32.2 (#59), Qwen3.5-9B: 14.4 (#143)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-9B |
|---|---|---|
| Terminal-Bench | 35.7% | 9.2% |
| Berkeley Function Calling Leaderboard | 59.1% | — |
| METR Time Horizons | 59.2% | — |
Reasoning Too close to call
Kimi K2 (Jul 2025): 22.7 (#173), Qwen3.5-9B: 22.5 (#178)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-9B |
|---|---|---|
| Epoch Capabilities Index | 146.02 | 139.45 |
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 12% |
| LMArena Hard Prompts | 1384 | — |
| DTBench | — | 71.2% |
| LMCA | — | 24.5% |
| ForecastBench | 60.2 | — |
Math Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 40.1 (#81), Qwen3.5-9B: 33.5 (#174)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-9B |
|---|---|---|
| MathArena Final-Answer Competitions | — | 48.5% |
| OTIS Mock AIME 2024-2025 | — | 61.7% |
| Omni-MATH | 65.4% | — |
| LMArena Math | 1396 | — |
| FrontierMath (Feb 2025 set) | 21.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3.5-9B leads
Kimi K2 (Jul 2025): 36.9 (#153), Qwen3.5-9B: 46.0 (#77)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-9B |
|---|---|---|
| GPQA Diamond | — | 79% |
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| Vectara Hallucination Rate | 17.9% | — |
| GPQA (HELM) | 65.3% | — |
| LMArena Expert | 1363 | — |
Multilingual Not comparable
Kimi K2 (Jul 2025): 49.8 (#125), Qwen3.5-9B: —
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-9B |
|---|---|---|
| LMArena Non-English | 1372 | — |
| LMArena Chinese | 1416 | — |
| LMArena French | 1379 | — |
| LMArena German | 1386 | — |
| LMArena Japanese | 1349 | — |
| LMArena Korean | 1324 | — |
| LMArena Russian | 1384 | — |
| LMArena Spanish | 1383 | — |
Instruction Following Not comparable
Kimi K2 (Jul 2025): 71.3 (#151), Qwen3.5-9B: —
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-9B |
|---|---|---|
| IFEval | 85% | — |
| LMArena Instruction Following | 1347 | — |
Long Context Not comparable
Kimi K2 (Jul 2025): 41.2 (#140), Qwen3.5-9B: —
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-9B |
|---|---|---|
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |
| LMArena Longer Query | 1353 | — |
Writing & Preference Not comparable
Kimi K2 (Jul 2025): 62.5 (#76), Qwen3.5-9B: —
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-9B |
|---|---|---|
| LMArena Text | 1380 | — |
| LMArena Creative Writing | 1349 | — |
| Short-Story Creative Writing | 85.6% | — |
| EQ-Bench Creative Writing | 1666 | — |
| WildBench | 86.2% | — |
| LMArena Multi-Turn | 1371 | — |
Frequently asked questions
Is Kimi K2 (Jul 2025) better than Qwen3.5-9B?
Kimi K2 (Jul 2025) is the stronger model overall, scoring 40.9 to 33.3 on the Noometry Index. Qwen3.5-9B costs 8.9× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.
Which is cheaper, Kimi K2 (Jul 2025) 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 (Jul 2025) lists at $0.57 and $2.30.
Is Kimi K2 (Jul 2025) or Qwen3.5-9B better for coding?
Kimi K2 (Jul 2025) scores higher on coding benchmarks: 43.1 versus 35.3 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Kimi K2 (Jul 2025) and Qwen3.5-9B share?
2 benchmarks have published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and Qwen3.5-9B has 10.