# Inkling 2 Small vs Qwen3.6-27B (slim)

> Qwen3.6-27B scores 66.7 (B) to Inkling 2 Small's 58.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b.md (~9,650 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b.json · canonical https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-12
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Qwen3.6-27B scores 66.7 (B) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 1 of 4 scored categories. Inkling 2 Small leads on risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- Inkling 2 Small: C 58.8, rank #102 of 161 open-weight models · https://www.anchorterminal.com/tools/inkling-2-small.min.md
- Qwen3.6-27B: B 66.7, rank #16 of 161 open-weight models · https://www.anchorterminal.com/tools/qwen3-6-27b.min.md
- Inkling 2 Small, good for Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image. Ahead on Risk, 65 against 55; Agent interface, 85 against 70; Documentation and upkeep, 67 against 31.
- Qwen3.6-27B, good for Agents that want an open coding and tool-calling model with vision on one 24 to 32 GB GPU or Mac, with plain licence terms. Ahead on Reach, 90 against 40.

| Category | Inkling 2 Small | Qwen3.6-27B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 40 | 90 |
| Risk (20%) | 65 | 55 |
| Agent interface (10%) | 85 | 70 |
| Documentation and upkeep (10%) | 67 | 31 |

| Fact (where they differ) | Inkling 2 Small | Qwen3.6-27B |
| --- | --- | --- |
| Vendor | Thinking Machines Lab | Alibaba (Qwen team) |
| Last release | 2026-11-12 | 2026-04-22 |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Reach, Qwen3.6-27B +50: Inkling 2 Small 40 (Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line.); Qwen3.6-27B 90 (Memory 25 of 30, Ollama's text-only 4-bit build is 17 GB and the vision build 18 GB, about 20 to 22 GB with a fifth added, which fits 24 GB.)
- Documentation and upkeep, Inkling 2 Small +36: Inkling 2 Small 67 (Model card 17 of 20, everything but a dated knowledge cut-off.); Qwen3.6-27B 31 (Model card 11 of 20, intended use, architecture, parameters and context are there, but limitations, languages and a knowledge cut-off aren't.)
- Agent interface, Inkling 2 Small +15: Inkling 2 Small 85 (Chat template 20, a Jinja file in the repository.); Qwen3.6-27B 70 (Chat template 20, a Jinja file in the repository.)
- Risk, Inkling 2 Small +10: Inkling 2 Small 65 (File safety 25, safetensors only and no repository code to run.); Qwen3.6-27B 55 (File safety 25, safetensors only and nothing from the repository runs to load it or build prompts.)
