# Qwen3.5-4B vs WeVisOne-VL-4B (slim)

> Qwen3.5-4B and WeVisOne-VL-4B score within a point of each other for open-weight models you run yourself, 61.2 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/qwen3-5-4b-vs-wevisone-vl-4b.md (~8,550 tokens) · this version ~580 tokens · JSON https://www.anchorterminal.com/compare/qwen3-5-4b-vs-wevisone-vl-4b.json · canonical https://www.anchorterminal.com/compare/qwen3-5-4b-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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Qwen3.5-4B and WeVisOne-VL-4B score within a point of each other on agent readiness, 61.2 (C) and 61 (C). WeVisOne-VL-4B leads on documentation and upkeep. Both do open-weight models you run yourself.

- Qwen3.5-4B: C 61.2, rank #38 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-4b.min.md
- WeVisOne-VL-4B: C 61, rank #84 of 160 open-weight models · https://www.anchorterminal.com/tools/wevisone-vl-4b.min.md
- Qwen3.5-4B, good for Agents that want a cheap local helper for tool calls, short reasoning and reading images on a laptop or small GPU Ahead on Reach, 85 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 Documentation and upkeep, 48 against 34.

| Category | Qwen3.5-4B | WeVisOne-VL-4B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 70 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 70 | 70 |
| Documentation and upkeep (10%) | 34 | 48 |

| Fact (where they differ) | Qwen3.5-4B | WeVisOne-VL-4B |
| --- | --- | --- |
| Vendor | Alibaba (Qwen team) | Tencent (WeChat Vision) |
| Last release | 2026-03-02 | 2026-10-27 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Reach, Qwen3.5-4B +15: Qwen3.5-4B 85 (Memory earns the full 30 because Ollama's own Q4_K_M build is 3.3 GB, about 4 GB with the fifth added, though Alibaba itself publishes no quantised 4B, so build…); 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.)
- Documentation and upkeep, WeVisOne-VL-4B +14: Qwen3.5-4B 34 (The card covers five of the seven items and misses limitations and a cut-off (14).); WeVisOne-VL-4B 48 (Model card 8, Intended use, limitations and the architecture are on the card.)