Kimi K2-Thinking-0905 vs Qwen3.6-27B: Specs & Benchmark Comparison
| Characteristic | Kimi K2-Thinking-0905 | Qwen3.6-27B |
|---|---|---|
| Company | Moonshot AI | Alibaba |
| Release Date | September 4, 2025 | April 21, 2026 |
| Parameters | 1.0T | 28B |
| Multimodal | No | Yes |
| Context (input) | 262K | 262K |
| Context (output) | 66K | 66K |
| Input Price / 1M | $0.60 | $0.60 |
| Output Price / 1M | $2.40 | $3.60 |
| Average Score | 0.9 | 1.0 |
Verdict
Both models show equal results — the choice depends on your specific use case.
Overall Performance
Both models show comparable average scores: Kimi K2-Thinking-0905 — 0.9, Qwen3.6-27B — 1.0.
API Cost
Kimi K2-Thinking-0905 is 1.4x cheaper: input $0.60/1M vs $0.60/1M tokens.
Context Window
Same context size: 262K tokens.
Recency
Qwen3.6-27B is newer: released 4/21/2026 vs 9/4/2025.
More About These Models
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Frequently Asked Questions
Which is better for coding — Kimi K2-Thinking-0905 or Qwen3.6-27B?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — Kimi K2-Thinking-0905 or Qwen3.6-27B?
Kimi K2-Thinking-0905 is cheaper for input: $0.60 per 1M tokens vs $0.60.
Which has a larger context window — Kimi K2-Thinking-0905 or Qwen3.6-27B?
Kimi K2-Thinking-0905 supports a larger context: 262,144 tokens vs 262,144.
The Kimi K2-Thinking-0905 and Qwen3.6-27B comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the Kimi K2-Thinking-0905 or Qwen3.6-27B page. See also the complete list of AI model comparisons.