# Qwen3.6-27B vs Ripple-65B Preview (slim)

> Qwen3.6-27B scores 66.7 (B) to Ripple-65B Preview's 53.3 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/qwen3-6-27b-vs-ripple-65b-preview.md (~7,650 tokens) · this version ~1,330 tokens · JSON https://www.anchorterminal.com/compare/qwen3-6-27b-vs-ripple-65b-preview.json · canonical https://www.anchorterminal.com/compare/qwen3-6-27b-vs-ripple-65b-preview
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-04
- 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 Ripple-65B Preview's 53.3 (D), and leads in 1 of 4 scored categories. Ripple-65B Preview leads on agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- Qwen3.6-27B: B 66.7, rank #16 of 121 open-weight models · https://www.anchorterminal.com/tools/qwen3-6-27b.min.md
- Ripple-65B Preview: D 53.3, rank #103 of 121 open-weight models · https://www.anchorterminal.com/tools/ripple-65b-preview.min.md
- 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 45.
- Ripple-65B Preview, good for Teams with Blackwell GPUs or a DGX Spark who want an Apache 2.0 coding model to try for terminal and agentic coding work, and can run the publisher's code to serve it. Ahead on Agent interface, 75 against 70; Documentation and upkeep, 49 against 31.

| Category | Qwen3.6-27B | Ripple-65B Preview |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 45 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 70 | 75 |
| Documentation and upkeep (10%) | 31 | 49 |

| Fact (where they differ) | Qwen3.6-27B | Ripple-65B Preview |
| --- | --- | --- |
| Vendor | Alibaba (Qwen team) | Ricursive Intelligence |
| Last release | 2026-04-22 | 2026-11-04 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Reach, Qwen3.6-27B +45: 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. Runtimes 25, released versions of llama.cpp, Ollama, vLLM, SGLang, LM Studio and Transformers all run the qwen3_5 architecture. Builds 10 of 15, Alibaba's only quantised build is FP8. Terms 15, Apache 2.0 with nothing added. Download 10, neither repository is gated. Hosted 5, three inference providers are live on Hugging Face and Alibaba's Model Studio serves it per the card.); Ripple-65B Preview 45 (Memory 10 of 30, the smallest 4-bit build is Ricursive's NVFP4 at 57.2 GB, 68.7 GB with a fifth added, which is over 64 GB and fits our reference machine. Runtimes 0, no released runtime runs the ricursive architecture with its own code; Ricursive's SGLang plugin and Transformers' remote code don't count. Builds 10, one quantised precision (NVFP4) from Ricursive. Terms 15, Apache 2.0 with nothing added. Download 10, not gated. Hosted 0, Ricursive serves no API, Hugging Face maps no provider, Together AI's page says coming soon, and GMI Cloud's and OpenRouter's pages weren't read.)
- Documentation and upkeep, Ripple-65B Preview +18: 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. Training data 5, only a general family description without a cut-off, in the GitHub README. Last change 5, the files last changed on 24 April 2026, 191 days before this check, and Qwen's GitHub repository holds only a README and licence, so no reference code of Alibaba's changed later. Responsiveness 0, Qwen answered none of the 40 most recent questions and reports, recounted on 1 November. Version policy 5, earlier and later 27B models stay in their own repositories without dated notes. File health 5, the files agree with the card but template and tool-calling reports wait without a reply.); Ripple-65B Preview 49 (Model card 14 of 20, no limitations and no knowledge cut-off. Training data 5, a general description with token counts and no cut-off. Last change 20, released today. Responsiveness 0, no discussions yet, read as none answered. Version policy 5, a first release, with the NVFP4 checkpoint replaced in place on release day under a commit note. File health 5, tokenizer_config.json carries a second, tool-less chat template and a 131,072-token limit against the card's 1M.)
- Agent interface, Ripple-65B Preview +5: Qwen3.6-27B 70 (Chat template 20, a Jinja file in the repository. Tool-calling format 10 of 25, the card names the qwen3_coder parser but the declaration and call format live only in the template. Trained tool calling 20, the template renders several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking turns off per request and comes back in think tags split out by the qwen3 parser. Context 10, 262,144 tokens native.); Ripple-65B Preview 75 (Chat template 20, chat_template.jinja in the repository. Tool-calling format 25, Ricursive's server README says how tools are declared and calls come back, with the ripple parser in SGLang 0.5.19. Trained tool calling 20, one or more calls a turn and agentic-coding RL. Structured output 0, not documented. Reasoning control 0, the template has no thinking switch or effort levels. Context 10, long-context training at 2M-token sequences for a stated 1M.)