# Qwen3.5-397B-A17B vs Ripple-65B Preview (slim)

> Qwen3.5-397B-A17B scores 64.1 (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/qwen3-5-397b-a17b-vs-ripple-65b-preview.md (~7,900 tokens) · this version ~1,330 tokens · JSON https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-ripple-65b-preview.json · canonical https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-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)

Qwen3.5-397B-A17B scores 64.1 (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.

- Qwen3.5-397B-A17B: B 64.1, rank #23 of 121 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-397b-a17b.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
- Qwen3.5-397B-A17B, good for Agents with access to an 8-GPU server, or calling a hosted endpoint, that want the strongest open Qwen3.5 with vision and a plain licence. Ahead on Reach, 70 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 34.

| Category | Qwen3.5-397B-A17B | Ripple-65B Preview |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 70 | 45 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 70 | 75 |
| Documentation and upkeep (10%) | 34 | 49 |

| Fact (where they differ) | Qwen3.5-397B-A17B | Ripple-65B Preview |
| --- | --- | --- |
| Vendor | Alibaba (Qwen team) | Ricursive Intelligence |
| Last release | 2026-02-16 | 2026-11-04 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Reach, Qwen3.5-397B-A17B +25: Qwen3.5-397B-A17B 70 (Memory scores 0, since even the smallest 4-bit build, LM Studio's MLX 4-bit at 223.9 GB, needs about 269 GB with a fifth added, and Alibaba's own GPTQ-Int4 about 283 GB. Runtimes reach the 25 cap on released llama.cpp, vLLM, SGLang and Transformers and LM Studio's catalogue, though Ollama has no local build. Alibaba's FP8 and GPTQ-Int4 builds give builds 15. Apache 2.0 with nothing added gives terms 15, the ungated repositories give download 10, and Alibaba's Model Studio plus five live providers on Hugging Face give hosted too its 5.); 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 +15: Qwen3.5-397B-A17B 34 (The card covers five of the seven items and misses limitations and a cut-off (14). Training data is a general description without a cut-off (5). The files last changed on 24 April 2026, 192 days before this check, past the 180-day band and within a year (5), and Qwen's GitHub repository holds only a README and licence, so no reference code of Alibaba's changed later. Alibaba answered none of the 40 most recent questions and reports, recounted on 2 November (0), and GitHub issues couldn't be counted. It's a first release at this size (5), and two template reports and a template fix still wait unanswered (5). 14 + 5 + 5 + 0 + 5 + 5 = 34.); 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: Qwen3.5-397B-A17B 70 (The template ships in the repository (20) and renders several tool calls per turn for a model trained for tool use (20). Tool-calling format gets 10, because the card names the qwen3_coder parser but leaves the declaration and call format to the template. Thinking turns off per request and comes back in think tags split by the qwen3 parser (10), and 262,144 tokens is native (10). Structured output scores 0, as nothing documents JSON output for the model.); 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.)