# Recursive Flint vs WeVisOne-VL-4B (slim)

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

- Full: https://www.anchorterminal.com/compare/recursive-flint-vs-wevisone-vl-4b.md (~9,650 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/recursive-flint-vs-wevisone-vl-4b.json · canonical https://www.anchorterminal.com/compare/recursive-flint-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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Recursive Flint and WeVisOne-VL-4B score within a point of each other on agent readiness, 61 (C) and 61 (C). Both do open-weight models you run yourself.

- Recursive Flint: C 61, rank #54 of 160 open-weight models · https://www.anchorterminal.com/tools/recursive-flint.min.md
- WeVisOne-VL-4B: C 61, rank #84 of 160 open-weight models · https://www.anchorterminal.com/tools/wevisone-vl-4b.min.md
- Recursive Flint, good for Agents doing repository work on a 32 to 48 GB Mac or NVIDIA box that want a sparse coder with documented tool calls and a plain licence. Ahead on Reach, 85 against 70; Risk, 60 against 55; Agent interface, 90 against 70; Documentation and upkeep, 67 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 | Recursive Flint | WeVisOne-VL-4B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 70 |
| Risk (20%) | 60 | 55 |
| Agent interface (10%) | 90 | 70 |
| Documentation and upkeep (10%) | 67 | 48 |

| Fact (where they differ) | Recursive Flint | WeVisOne-VL-4B |
| --- | --- | --- |
| Vendor | Recursive | Tencent (WeChat Vision) |
| Last release | 2026-10-21 | 2026-10-27 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 3.5/5 (4) | none |

Why the edge:
- Agent interface, Recursive Flint +20: Recursive Flint 90 (Chat template 20, a Jinja file in the repository and inside both GGUFs.); WeVisOne-VL-4B 70 (Chat template 20, chat_template.jinja in the repository (5,292 characters), Qwen3-VL's template.)
- Documentation and upkeep, Recursive Flint +19: Recursive Flint 67 (Model card 17 of 20, everything but languages.); WeVisOne-VL-4B 48 (Model card 8, Intended use, limitations and the architecture are on the card.)
- Reach, Recursive Flint +15: Recursive Flint 85 (Memory 20 of 30, Recursive's MLX INT4 build is 22.6 GB, or 27.1 GB with a fifth added, which fits 32 GB, and every other 4-bit build lands in the same band.); 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.)
- Risk, Recursive Flint +5: Recursive Flint 60 (File safety 15 of 25, safetensors and GGUF only, but the card's documented BF16 route installs the wheel shipped in the repository.); WeVisOne-VL-4B 55 (File safety 15, the backbone is safetensors, but mask_decoder.pt, a PyTorch pickle the card calls a required component, sits beside it.)