Model comparison
Kimi K2 (Jul 2025) vs Qwen3-VL 235B-A22B
Qwen3-VL 235B-A22B is the stronger model overall, scoring 43.2 to 41.2 on the Noometry Index.
Last verified . 17 shared benchmarks.
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. Kimi K2 (Jul 2025) scores higher in 2 categories and Qwen3-VL 235B-A22B in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3-VL 235B-A22B leads 29.3 to 23.3.
- Kimi K2 (Jul 2025) is cheaper at $0.57 / $2.30 per million input/output tokens, against $0.70 / $2.80 for Qwen3-VL 235B-A22B.
- Kimi K2 (Jul 2025) accepts more context: 262K tokens versus 131K.
Side by side
| Kimi K2 (Jul 2025) | Qwen3-VL 235B-A22B | |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 41.2 | 43.2 |
| Released | 2025-07-12 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 262K | 33K |
| Input $ / M tokens | $0.57 | $0.70 |
| Output $ / M tokens | $2.30 | $2.80 |
| Results tracked | 42 | 18 |
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Category by category
Coding Too close to call
Kimi K2 (Jul 2025): 42.4 (#102), Qwen3-VL 235B-A22B: 42.4 (#100)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Coding | 1399 | 1439 |
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| GSO | 4.9% | — |
| WeirdML | 42.8% | — |
| ALE-Bench | 597.5 | — |
Agentic & Tool Use Not comparable
Kimi K2 (Jul 2025): 32.4 (#64), Qwen3-VL 235B-A22B: —
| Benchmark | Kimi K2 (Jul 2025) | Qwen3-VL 235B-A22B |
|---|---|---|
| Terminal-Bench | 35.7% | — |
| Berkeley Function Calling Leaderboard | 59.1% | — |
| METR Time Horizons | 59.2% | — |
Reasoning Qwen3-VL 235B-A22B leads
Kimi K2 (Jul 2025): 23.3 (#179), Qwen3-VL 235B-A22B: 29.3 (#92)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Hard Prompts | 1384 | 1428 |
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| Epoch Capabilities Index | 146.01 | — |
| ForecastBench | 60.2 | — |
Math Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 42.7 (#83), Qwen3-VL 235B-A22B: 39.0 (#118)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Math | 1397 | 1426 |
| Omni-MATH | 65.4% | — |
| FrontierMath (Feb 2025 set) | 21.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3-VL 235B-A22B leads
Kimi K2 (Jul 2025): 37.3 (#157), Qwen3-VL 235B-A22B: 40.3 (#121)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Expert | 1365 | 1442 |
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| Vectara Hallucination Rate | 17.9% | — |
| GPQA (HELM) | 65.3% | — |
Multimodal Not comparable
Kimi K2 (Jul 2025): —, Qwen3-VL 235B-A22B: 39.8 (#55)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Vision | — | 1247 |
Multilingual Qwen3-VL 235B-A22B leads
Kimi K2 (Jul 2025): 49.6 (#130), Qwen3-VL 235B-A22B: 51.9 (#97)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Non-English | 1372 | 1405 |
| LMArena Chinese | 1415 | 1463 |
| LMArena French | 1379 | 1452 |
| LMArena German | 1387 | 1424 |
| LMArena Japanese | 1349 | 1385 |
| LMArena Korean | 1325 | 1394 |
| LMArena Russian | 1385 | 1408 |
| LMArena Spanish | 1386 | 1428 |
Instruction Following Qwen3-VL 235B-A22B leads
Kimi K2 (Jul 2025): 71.1 (#156), Qwen3-VL 235B-A22B: 74.2 (#101)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Instruction Following | 1348 | 1406 |
| IFEval | 85% | — |
Long Context Qwen3-VL 235B-A22B leads
Kimi K2 (Jul 2025): 41.2 (#145), Qwen3-VL 235B-A22B: 43.4 (#98)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Longer Query | 1353 | 1420 |
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |
Writing & Preference Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 62.3 (#78), Qwen3-VL 235B-A22B: 60.2 (#99)
| Benchmark | Kimi K2 (Jul 2025) | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Text | 1380 | 1420 |
| LMArena Creative Writing | 1350 | 1366 |
| LMArena Multi-Turn | 1371 | 1428 |
| 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-VL 235B-A22B?
Qwen3-VL 235B-A22B is the stronger model overall, scoring 43.2 to 41.2 on the Noometry Index.
Which is cheaper, Kimi K2 (Jul 2025) or Qwen3-VL 235B-A22B?
Kimi K2 (Jul 2025) is cheaper. It lists at $0.57 per million input tokens and $2.30 per million output tokens; Qwen3-VL 235B-A22B lists at $0.70 and $2.80.
Is Kimi K2 (Jul 2025) or Qwen3-VL 235B-A22B better for coding?
They score almost the same on coding (42.4 vs 42.4); test both on your own repository before choosing.
Which has the bigger context window?
Kimi K2 (Jul 2025) does, with 262K tokens against 131K.
How many benchmarks do Kimi K2 (Jul 2025) and Qwen3-VL 235B-A22B share?
17 benchmarks have published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and Qwen3-VL 235B-A22B has 18.