# Granite 4.2 3B vs WeVisOne-VL-4B (slim)

> WeVisOne-VL-4B scores 61 (C) to Granite 4.2 3B's 59.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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- 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 Granite 4.2 3B's 59.8 (C), and leads in 0 of 4 scored categories. Granite 4.2 3B leads on reach, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- Granite 4.2 3B: C 59.8, rank #92 of 160 open-weight models · https://www.anchorterminal.com/tools/granite-4-2-3b.min.md
- WeVisOne-VL-4B: C 61, rank #84 of 160 open-weight models · https://www.anchorterminal.com/tools/wevisone-vl-4b.min.md
- Granite 4.2 3B, good for Agents on small hardware that want a permissive reasoning model for tool calls and coding, with thinking they can switch off Ahead on Reach, 95 against 70; Agent interface, 85 against 70; Documentation and upkeep, 92 against 48.
- 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

| Category | Granite 4.2 3B | WeVisOne-VL-4B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 95 | 70 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 85 | 70 |
| Documentation and upkeep (10%) | 92 | 48 |

| Fact (where they differ) | Granite 4.2 3B | WeVisOne-VL-4B |
| --- | --- | --- |
| Vendor | IBM | Tencent (WeChat Vision) |
| Last release | 2026-10-20 | 2026-10-27 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 3.8/5 (4) | none |

Why the edge:
- Documentation and upkeep, Granite 4.2 3B +44: Granite 4.2 3B 92 (The card covers everything but a knowledge cut-off (17).); WeVisOne-VL-4B 48 (Model card 8, Intended use, limitations and the architecture are on the card.)
- Reach, Granite 4.2 3B +25: Granite 4.2 3B 95 (Memory earns the full 30, since IBM's 4-bit MLX build is 2.07 GB and Ollama's Q4_K_M build 2.2 GB, about 2.5 to 2.6 GB with the fifth added.); 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, Granite 4.2 3B +15: Granite 4.2 3B 85 (The template ships in the repository (20).); WeVisOne-VL-4B 70 (Chat template 20, chat_template.jinja in the repository (5,292 characters), Qwen3-VL's template.)