Qwen3.8 27B vs Kimi K2.6 vs Inkling Small
Too close to call on our weighted score (Inkling Small 68, Qwen3.8 27B 66, Kimi K2.6 64). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3.8 27B
66/100- ECI151.8
- Price$0.40 / $2.55
- Context262K
Moonshot AIKimi K2.6
64/100- ECI151.1
- Price$0.95 / $4.00
- Context262K
Thinking MachinesInkling Small
68/100- ECI150.5
- Price$0.58 / $1.44
- Context1.05M
Too close to call
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%.
- CapabilityQwen3.8 27BCapabilities Index (ECI): Qwen3.8 27B 151.8 · Kimi K2.6 151.1 · Inkling Small 150.5
- Lowest priceInkling SmallInkling Small $0.795 · Qwen3.8 27B $0.938 · Kimi K2.6 $1.71 per 1M tokens (3:1 blend)
- Longest contextInkling SmallInkling Small 1,048,576 · Qwen3.8 27B 262,144 · Kimi K2.6 262,144 tokens
- Widest inputsSame inputsQwen3.8 27B: Text, Images, Video · Kimi K2.6: Text, Images, Video · Inkling Small: Text, Images, Audio
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3.8 27B | Kimi K2.6 | Inkling Small |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 79 | 78 | 77 |
| Price | 25% | 49 | 37 | 52 |
| Inputs & features | 15% | 70 | 80 | 70 |
| Context window | 10% | 37 | 37 | 61 |
| Overall | 100% | 66/100 | 64/100 | 68/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.8 27BAlibaba (Qwen) | Kimi K2.6Moonshot AI | Inkling SmallThinking Machines |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 151.8 (best) | 151.1 | 150.5 |
| ECI rank | #54 of 165 (best) | #55 of 165 | #58 of 165 |
| GPQA DiamondGraduate-level science questions | — | 90.8% (best) | 88.5% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 57.2% (best) | 46.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 96.1% (best) | 90.0% |
| SWE-bench VerifiedFixing real GitHub issues | — | 76.7% | — |
| SimpleQA VerifiedShort factual questions | — | 34.9% (best) | 19.1% |
| Price per million tokens | |||
| Input | $0.40 (best) | $0.95 | $0.58 |
| Output | $2.55 | $4.00 | $1.44 (best) |
| Cached input | — | $0.16 | $0.116 (best) |
| Blended (3:1) | $0.938 | $1.71 | $0.795 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 49 providers | Official Moonshot AI API | Official Thinking Machines API |
| Limits | |||
| Context window | 262,144 tokens | 262,144 tokens | 1,048,576 tokens (best) |
| Max output | 32,768 tokens | 262,144 tokens | 1,048,576 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | Yes | Yes | No |
| Reasoning | Yes | Yes | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Open | OpenApache-2.0 |
| API model ID | — | kimi-k2.6 | thinkingmachines/Inkling-Small |
| API providers | 53 | 60 (best) | 12 |
| Released | Aug 14, 2026 | Apr 20, 2026 | Jul 30, 2026 |
| Knowledge cutoff | — | Jan 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3.8 27B$9.10
- Kimi K2.6$17.50
- Inkling Small$8.68
Which should you choose?
Which is better: Qwen3.8 27B, Kimi K2.6 or Inkling Small?
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%.
Which is cheaper, Qwen3.8 27B, Kimi K2.6 or Inkling Small?
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).
Which scores higher on benchmarks?
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.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.8 27B and Inkling Small 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.
Which has the bigger context window?
Inkling Small has the largest context window at 1,048,576 tokens, against 262,144 for Qwen3.8 27B and 262,144 for Kimi K2.6. Maximum output per response: Qwen3.8 27B up to 32,768, Kimi K2.6 up to 262,144, Inkling Small up to 1,048,576 tokens.
Which can read images, PDFs, audio or video?
Qwen3.8 27B accepts text, images and video; Kimi K2.6 accepts text, images and video; Inkling Small accepts text, images and audio. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
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.
How do you decide the winner?
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.
