Inkling Small vs Kimi K2.6 vs Qwen3.8 27B

It is close. Our weighted score puts them within 2 points (Inkling Small 68/100, Qwen3.8 27B 66/100, Kimi K2.6 64/100), so choose by what matters most for your work: Qwen3.8 27B for raw capability, Inkling Small on price and Inkling Small for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Inkling Small is cheaper at $0.58 input / $1.44 output per million tokens (official Thinking Machines API price). Qwen3.8 27B costs $0.40 input / $2.55 output per million tokens (median across 49 API providers); Kimi K2.6 costs $0.95 input / $4.00 output per million tokens (official Moonshot AI API price). At a typical mix of three input tokens to one output token, that is $0.795 per million tokens for Inkling Small versus $0.938 for Qwen3.8 27B (1.2× as much) and $1.71 for Kimi K2.6 (2.2× as much).

Qwen3.8 27B scores higher on the Capabilities Index (ECI): Qwen3.8 27B 151.8 (#54 of 165), Kimi K2.6 151.1 (#55 of 165) and Inkling Small 150.5 (#58 of 165). The confidence ranges of the top two overlap (149.9–153.6 vs 149.1–152.9), so treat the gap as small.

There are no published SWE-bench Verified results for Inkling Small and Qwen3.8 27B yet, so there is no like-for-like coding score. On overall capability, Qwen3.8 27B leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Inkling Small has the largest context window at 1,048,576 tokens, against 262,144 for Kimi K2.6 and 262,144 for Qwen3.8 27B. Maximum output per response: Inkling Small up to 1,048,576, Kimi K2.6 up to 262,144, Qwen3.8 27B up to 32,768 tokens.

Inkling Small accepts text, images and audio; Kimi K2.6 accepts text, images and video; Qwen3.8 27B accepts text, images and video. They handle the same number of input types.

Yes, all three publish their weights (Apache-2.0), so you can self-host them.

Qwen3.8 27B is the newest, released Aug 14, 2026. Inkling Small came out Jul 30, 2026; Kimi K2.6 came out Apr 20, 2026. Knowledge cutoff: Kimi K2.6 Jan 2025.

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.