# Ripple-65B Preview vs WeVisOne-VL-4B (slim)

> WeVisOne-VL-4B scores 61 (C) 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/ripple-65b-preview-vs-wevisone-vl-4b.md (~8,900 tokens) · this version ~580 tokens · JSON https://www.anchorterminal.com/compare/ripple-65b-preview-vs-wevisone-vl-4b.json · canonical https://www.anchorterminal.com/compare/ripple-65b-preview-vs-wevisone-vl-4b
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
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WeVisOne-VL-4B scores 61 (C) 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. Both do open-weight models you run yourself.

- Ripple-65B Preview: D 53.3, rank #135 of 160 open-weight models · https://www.anchorterminal.com/tools/ripple-65b-preview.min.md
- WeVisOne-VL-4B: C 61, rank #84 of 160 open-weight models · https://www.anchorterminal.com/tools/wevisone-vl-4b.min.md
- 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.
- WeVisOne-VL-4B, good for Agents that need to locate, count or cut out objects in images on a small GPU, under a permissive licence Ahead on Reach, 70 against 45.

| Category | Ripple-65B Preview | WeVisOne-VL-4B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 45 | 70 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 75 | 70 |
| Documentation and upkeep (10%) | 49 | 48 |

| Fact (where they differ) | Ripple-65B Preview | WeVisOne-VL-4B |
| --- | --- | --- |
| Vendor | Ricursive Intelligence | Tencent (WeChat Vision) |
| Last release | 2026-11-04 | 2026-10-27 |

Why the edge:
- Reach, WeVisOne-VL-4B +25: 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.); WeVisOne-VL-4B 70 (Memory 30, the only build from Tencent is the BF16 safetensors file with its decoder, 9.7 GB, and 9.7 GB × 1.2 = 11.6 GB, within 16 GB.)
- Agent interface, Ripple-65B Preview +5: Ripple-65B Preview 75 (Chat template 20, chat_template.jinja in the repository.); WeVisOne-VL-4B 70 (Chat template 20, chat_template.jinja in the repository (5,292 characters), Qwen3-VL's template.)