Model comparison
Kimi K2.7 Code vs Qwen3.6 35B-A3B
Kimi K2.7 Code is the stronger model overall, scoring 43.0 to 37.2 on the Noometry Index. Qwen3.6 35B-A3B costs 3.1× less per token, which makes it the better buy when Kimi K2.7 Code'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 K2.7 Code scores higher in 5 categories and Qwen3.6 35B-A3B in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.7 Code leads 52.6 to 37.9.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 54% for Kimi K2.7 Code and 20.4% for Qwen3.6 35B-A3B.
- Qwen3.6 35B-A3B is cheaper at $0.25 / $1.49 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
Side by side
| Kimi K2.7 Code | Qwen3.6 35B-A3B | |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 43.0 | 37.2 |
| Released | 2026-06-12 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 262K | 66K |
| Input $ / M tokens | $0.95 | $0.25 |
| Output $ / M tokens | $4 | $1.49 |
| Results tracked | 19 | 14 |
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Category by category
Coding Kimi K2.7 Code leads
Kimi K2.7 Code: 42.4 (#92), Qwen3.6 35B-A3B: 36.7 (#190)
| Benchmark | Kimi K2.7 Code | Qwen3.6 35B-A3B |
|---|---|---|
| SciCode | 47.5% | 35.8% |
| WeirdML | 54.1% | 34.5% |
| DeepSWE | 30.5% | — |
| FrontierCode | 30.1% | — |
| LMArena WebDev | 1473 | — |
| ALE-Bench | 886.23 | — |
Agentic & Tool Use Kimi K2.7 Code leads
Kimi K2.7 Code: 23.9 (#115), Qwen3.6 35B-A3B: 21.9 (#126)
| Benchmark | Kimi K2.7 Code | Qwen3.6 35B-A3B |
|---|---|---|
| Terminal-Bench | — | 23% |
| APEX-Agents | 37.6% | — |
| GBAEval | 0.9% | — |
| Vending-Bench 2 | 5,083 | — |
Reasoning Kimi K2.7 Code leads
Kimi K2.7 Code: 38.2 (#56), Qwen3.6 35B-A3B: 27.2 (#112)
| Benchmark | Kimi K2.7 Code | Qwen3.6 35B-A3B |
|---|---|---|
| CritPt | 10% | 0.3% |
| Chess Puzzles | 21% | 26% |
| Surface Evolver Bench | 48.8% | 44.4% |
| Epoch Capabilities Index | 150.01 | 143.92 |
| SimpleBench | 57.9% | — |
| NYT Connections (extended) | — | 41.6% |
| Mystery Game Puzzles | — | 22% |
| DTBench | — | 73.9% |
| LMCA | — | 29.7% |
Math Kimi K2.7 Code leads
Kimi K2.7 Code: 52.6 (#39), Qwen3.6 35B-A3B: 37.9 (#90)
| Benchmark | Kimi K2.7 Code | Qwen3.6 35B-A3B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 54% | 20.4% |
| OTIS Mock AIME 2024-2025 | 95.6% | 86.7% |
| FrontierMath Tier 4 | 12.2% | — |
Knowledge Kimi K2.7 Code leads
Kimi K2.7 Code: 53.6 (#51), Qwen3.6 35B-A3B: 51.4 (#63)
| Benchmark | Kimi K2.7 Code | Qwen3.6 35B-A3B |
|---|---|---|
| GPQA Diamond | 87.9% | 84.8% |
| SimpleQA Verified | 36.5% | — |
Frequently asked questions
Is Kimi K2.7 Code better than Qwen3.6 35B-A3B?
Kimi K2.7 Code is the stronger model overall, scoring 43.0 to 37.2 on the Noometry Index. Qwen3.6 35B-A3B costs 3.1× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.
Which is cheaper, Kimi K2.7 Code or Qwen3.6 35B-A3B?
Qwen3.6 35B-A3B is cheaper. It lists at $0.25 per million input tokens and $1.49 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.
Is Kimi K2.7 Code or Qwen3.6 35B-A3B better for coding?
Kimi K2.7 Code scores higher on coding benchmarks: 42.4 versus 36.7 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Kimi K2.7 Code and Qwen3.6 35B-A3B share?
9 benchmarks have published results for both models. Kimi K2.7 Code has 19 scored results on Noometry and Qwen3.6 35B-A3B has 14.