Model comparison
Kimi K2.7 Code vs Qwen3 235B-A22B
Kimi K2.7 Code and Qwen3 235B-A22B score almost the same on the Noometry Index (43.3 vs 43.5), so choose on price, context window or the category you care about most.
Last verified . 10 shared benchmarks.
Alibaba (Qwen)Summary
- They share 10 benchmarks with published results for both. Kimi K2.7 Code scores higher in 3 categories and Qwen3 235B-A22B in 2 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Kimi K2.7 Code leads 39.0 to 15.7.
- The biggest single-benchmark swing is SimpleBench: 57.9% for Kimi K2.7 Code and 31% for Qwen3 235B-A22B.
- Qwen3 235B-A22B is cheaper at $0.70 / $2.80 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
- Kimi K2.7 Code accepts more context: 262K tokens versus 131K.
Side by side
| Kimi K2.7 Code | Qwen3 235B-A22B | |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 43.3 | 43.5 |
| Released | 2026-06-12 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 262K | 16K |
| Input $ / M tokens | $0.95 | $0.70 |
| Output $ / M tokens | $4 | $2.80 |
| Results tracked | 19 | 49 |
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Category by category
Coding Qwen3 235B-A22B leads
Kimi K2.7 Code: 42.9 (#95), Qwen3 235B-A22B: 44.3 (#75)
| Benchmark | Kimi K2.7 Code | Qwen3 235B-A22B |
|---|---|---|
| SciCode | 47.5% | 42.4% |
| WeirdML | 54.1% | 41% |
| DeepSWE | 30.5% | — |
| FrontierCode | 30.1% | — |
| Aider Polyglot | — | 59.6% |
| LMArena WebDev | 1473 | — |
| LMArena Coding | — | 1445 |
| ALE-Bench | 886.23 | — |
Agentic & Tool Use Qwen3 235B-A22B leads
Kimi K2.7 Code: 24.0 (#122), Qwen3 235B-A22B: 33.9 (#51)
| Benchmark | Kimi K2.7 Code | Qwen3 235B-A22B |
|---|---|---|
| Vending-Bench 2 | 5,083 | -11.34 |
| APEX-Agents | 37.6% | — |
| Berkeley Function Calling Leaderboard | — | 52.1% |
| GBAEval | 0.9% | — |
Reasoning Kimi K2.7 Code leads
Kimi K2.7 Code: 39.0 (#61), Qwen3 235B-A22B: 15.7 (#311)
| Benchmark | Kimi K2.7 Code | Qwen3 235B-A22B |
|---|---|---|
| SimpleBench | 57.9% | 31% |
| CritPt | 10% | 0% |
| Chess Puzzles | 21% | 12% |
| Epoch Capabilities Index | 149.97 | 143.85 |
| ARC-AGI-2 | — | 1.3% |
| Kagi LLM Benchmark | — | 69.4% |
| ARC-AGI-1 | — | 11% |
| LMArena Hard Prompts | — | 1433 |
| Mystery Game Puzzles | — | 9% |
| DTBench | — | 80.3% |
| LMCA | — | 29.3% |
| Surface Evolver Bench | 48.8% | — |
| ForecastBench | — | 59.7 |
Math Kimi K2.7 Code leads
Kimi K2.7 Code: 52.9 (#48), Qwen3 235B-A22B: 50.4 (#57)
| Benchmark | Kimi K2.7 Code | Qwen3 235B-A22B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 95.6% | 86.7% |
| FrontierMath (Tiers 1-3) | 54% | — |
| FrontierMath Tier 4 | 12.2% | — |
| Omni-MATH | — | 71.8% |
| LMArena Math | — | 1432 |
| MATH Level 5 | — | 68.9% |
| FrontierMath (Feb 2025 set) | — | 8.5% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Kimi K2.7 Code leads
Kimi K2.7 Code: 53.5 (#57), Qwen3 235B-A22B: 49.6 (#73)
| Benchmark | Kimi K2.7 Code | Qwen3 235B-A22B |
|---|---|---|
| GPQA Diamond | 87.9% | 80.1% |
| SimpleQA Verified | 36.5% | 40.4% |
| MMLU-Pro | — | 84.4% |
| Confabulations | — | 15.6% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 72.7% |
| LMArena Expert | — | 1463 |
Multilingual Not comparable
Kimi K2.7 Code: —, Qwen3 235B-A22B: 52.3 (#89)
| Benchmark | Kimi K2.7 Code | Qwen3 235B-A22B |
|---|---|---|
| LMArena Non-English | — | 1409 |
| LMArena Chinese | — | 1481 |
| LMArena French | — | 1445 |
| LMArena German | — | 1433 |
| LMArena Japanese | — | 1399 |
| LMArena Korean | — | 1391 |
| LMArena Russian | — | 1411 |
| LMArena Spanish | — | 1430 |
Instruction Following Not comparable
Kimi K2.7 Code: —, Qwen3 235B-A22B: 72.6 (#136)
| Benchmark | Kimi K2.7 Code | Qwen3 235B-A22B |
|---|---|---|
| IFEval | — | 83.5% |
| LMArena Instruction Following | — | 1408 |
Long Context Not comparable
Kimi K2.7 Code: —, Qwen3 235B-A22B: 46.1 (#26)
| Benchmark | Kimi K2.7 Code | Qwen3 235B-A22B |
|---|---|---|
| Fiction.LiveBench | — | 75% |
| LMArena Longer Query | — | 1426 |
Writing & Preference Not comparable
Kimi K2.7 Code: —, Qwen3 235B-A22B: 59.6 (#108)
| Benchmark | Kimi K2.7 Code | Qwen3 235B-A22B |
|---|---|---|
| LMArena Text | — | 1419 |
| LMArena Creative Writing | — | 1384 |
| Short-Story Creative Writing | — | 83% |
| EQ-Bench Creative Writing | — | 1366 |
| WildBench | — | 86.6% |
| LMArena Multi-Turn | — | 1432 |
Frequently asked questions
Is Kimi K2.7 Code better than Qwen3 235B-A22B?
Kimi K2.7 Code and Qwen3 235B-A22B score almost the same on the Noometry Index (43.3 vs 43.5), so choose on price, context window or the category you care about most.
Which is cheaper, Kimi K2.7 Code or Qwen3 235B-A22B?
Qwen3 235B-A22B is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.
Is Kimi K2.7 Code or Qwen3 235B-A22B better for coding?
Qwen3 235B-A22B scores higher on coding benchmarks: 44.3 versus 42.9 in the Noometry coding category.
Which has the bigger context window?
Kimi K2.7 Code does, with 262K tokens against 131K.
How many benchmarks do Kimi K2.7 Code and Qwen3 235B-A22B share?
10 benchmarks have published results for both models. Kimi K2.7 Code has 19 scored results on Noometry and Qwen3 235B-A22B has 49.