Model comparison
Kimi K2 (Jul 2025) vs Qwen3.5-Flash
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 41.2 on the Noometry Index.
Last verified . 22 shared benchmarks.
Alibaba (Qwen)Summary
- They share 22 benchmarks with published results for both. Kimi K2 (Jul 2025) scores higher in 3 categories and Qwen3.5-Flash in 5 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.5-Flash leads 33.7 to 23.3.
- The biggest single-benchmark swing is Vectara Hallucination Rate: 17.9% for Kimi K2 (Jul 2025) and 10.5% for Qwen3.5-Flash.
- Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.57 / $2.30 for Kimi K2 (Jul 2025).
- Qwen3.5-Flash accepts more context: 1M tokens versus 262K.
- Kimi K2 (Jul 2025) has downloadable open weights; the other is API-only.
Side by side
| Kimi K2 (Jul 2025) | Qwen3.5-Flash | |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 41.2 | 42.5 |
| Released | 2025-07-12 | 2026-02-23 |
| Weights | Open | Proprietary |
| Context window | 262K | 1M |
| Max output | 262K | 66K |
| Input $ / M tokens | $0.57 | $0.10 |
| Output $ / M tokens | $2.30 | $0.40 |
| Results tracked | 42 | 32 |
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Category by category
Coding Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 42.4 (#102), Qwen3.5-Flash: 34.2 (#242)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-Flash |
|---|---|---|
| LMArena Coding | 1399 | 1412 |
| ALE-Bench | 597.5 | 221.8 |
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| LMArena WebDev | — | 1244 |
| GSO | 4.9% | — |
| WeirdML | 42.8% | — |
Agentic & Tool Use Not comparable
Kimi K2 (Jul 2025): 32.4 (#64), Qwen3.5-Flash: —
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-Flash |
|---|---|---|
| Terminal-Bench | 35.7% | — |
| Berkeley Function Calling Leaderboard | 59.1% | — |
| METR Time Horizons | 59.2% | — |
| Vending-Bench 2 | — | 462.69 |
Reasoning Qwen3.5-Flash leads
Kimi K2 (Jul 2025): 23.3 (#179), Qwen3.5-Flash: 33.7 (#72)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-Flash |
|---|---|---|
| LMArena Hard Prompts | 1384 | 1403 |
| Epoch Capabilities Index | 146.01 | 143.98 |
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| Chess Puzzles | — | 21% |
| Mystery Game Puzzles | — | 20% |
| DTBench | — | 82.9% |
| LMCA | — | 29.1% |
| ForecastBench | 60.2 | — |
Math Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 42.7 (#83), Qwen3.5-Flash: 37.4 (#158)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-Flash |
|---|---|---|
| LMArena Math | 1397 | 1407 |
| FrontierMath (Feb 2025 set) | 21.4% | 6.2% |
| FrontierMath Tier 4 (v1) | 0% | 0% |
| FrontierMath (Tiers 1-3) | — | 18.2% |
| OTIS Mock AIME 2024-2025 | — | 84.4% |
| Omni-MATH | 65.4% | — |
Knowledge Qwen3.5-Flash leads
Kimi K2 (Jul 2025): 37.3 (#157), Qwen3.5-Flash: 43.2 (#93)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-Flash |
|---|---|---|
| Vectara Hallucination Rate | 17.9% | 10.5% |
| LMArena Expert | 1365 | 1407 |
| GPQA Diamond | — | 82.3% |
| SimpleQA Verified | — | 20.3% |
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| GPQA (HELM) | 65.3% | — |
Multilingual Too close to call
Kimi K2 (Jul 2025): 49.6 (#130), Qwen3.5-Flash: 50.5 (#121)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-Flash |
|---|---|---|
| LMArena Non-English | 1372 | 1385 |
| LMArena Chinese | 1415 | 1446 |
| LMArena French | 1379 | 1412 |
| LMArena German | 1387 | 1390 |
| LMArena Japanese | 1349 | 1368 |
| LMArena Korean | 1325 | 1344 |
| LMArena Russian | 1385 | 1379 |
| LMArena Spanish | 1386 | 1400 |
Instruction Following Qwen3.5-Flash leads
Kimi K2 (Jul 2025): 71.1 (#156), Qwen3.5-Flash: 72.6 (#139)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-Flash |
|---|---|---|
| LMArena Instruction Following | 1348 | 1374 |
| IFEval | 85% | — |
Long Context Qwen3.5-Flash leads
Kimi K2 (Jul 2025): 41.2 (#145), Qwen3.5-Flash: 42.4 (#124)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-Flash |
|---|---|---|
| LMArena Longer Query | 1353 | 1392 |
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |
Writing & Preference Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 62.3 (#78), Qwen3.5-Flash: 57.9 (#122)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3.5-Flash |
|---|---|---|
| LMArena Text | 1380 | 1397 |
| LMArena Creative Writing | 1350 | 1343 |
| LMArena Multi-Turn | 1371 | 1393 |
| 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-Flash?
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 41.2 on the Noometry Index.
Which is cheaper, Kimi K2 (Jul 2025) or Qwen3.5-Flash?
Qwen3.5-Flash is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Kimi K2 (Jul 2025) lists at $0.57 and $2.30.
Is Kimi K2 (Jul 2025) or Qwen3.5-Flash better for coding?
Kimi K2 (Jul 2025) scores higher on coding benchmarks: 42.4 versus 34.2 in the Noometry coding category.
Which has the bigger context window?
Qwen3.5-Flash does, with 1M tokens against 262K.
How many benchmarks do Kimi K2 (Jul 2025) and Qwen3.5-Flash share?
22 benchmarks have published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and Qwen3.5-Flash has 32.