Kimi K2.6 versus Qwen3.6 27B

Two models head to head

Kimi K2.6 and Qwen3.6 27B are two open-weight models that you can install on your own servers, one from Moonshot AI, the other from Alibaba Cloud (Qwen). Kimi K2.6 was released on April 20, 2026, Qwen3.6 27B on April 22, 2026.

All figures below come from public sources checked on October 22, 2026: models.dev and OpenRouter for prices and capabilities, Epoch AI for scores.

Which one is more capable?

On our capability index, Kimi K2.6 scores 84.4 out of 100 and Qwen3.6 27B 72.2. Kimi K2.6 leads by 12.2 points.

On the 3 benchmarks reported for both, Kimi K2.6 wins 3 times and Qwen3.6 27B 0:

• GPQA Diamond (PhD-level science questions): Kimi K2.6 90.8%, Qwen3.6 27B 85.9%
• OTIS Mock AIME (competition mathematics problems): Kimi K2.6 96.1%, Qwen3.6 27B 91.1%
• FrontierMath (very hard research-level mathematics): Kimi K2.6 57.2%, Qwen3.6 27B 35.1%

Pricing

Kimi K2.6 costs $0.95 per million input tokens and $4 per million output tokens; Qwen3.6 27B costs $0.33 and $2.7.

For a typical agent task (read 20,000 tokens, write 2,000), expect $0.027 with Kimi K2.6 versus $0.012 with Qwen3.6 27B. Qwen3.6 27B is 2.3 times cheaper, a gap that adds up quickly over 1,000 tasks: $15.1 difference.

Run the numbers with your own volumes in the agent cost calculator.

Context and capabilities

Both models have the same context window: 262,144 tokens, roughly 393 pages.

Reasoning mode: Kimi K2.6 yes, Qwen3.6 27B yes. Tool calling: Kimi K2.6 yes, Qwen3.6 27B yes. Image input: Kimi K2.6 yes, Qwen3.6 27B yes.

Both publish their weights: you can host them yourself.

In short

Our reading of the data:

• Choose Kimi K2.6 for a higher capability index.
• Choose Qwen3.6 27B for a lower cost.

This verdict relies on public figures; it does not replace a trial on your own tasks.