# Darwin-36B-Opus vs WeVisOne-VL-4B (slim)

> Darwin-36B-Opus 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/darwin-36b-opus-vs-wevisone-vl-4b.md (~8,950 tokens) · this version ~580 tokens · JSON https://www.anchorterminal.com/compare/darwin-36b-opus-vs-wevisone-vl-4b.json · canonical https://www.anchorterminal.com/compare/darwin-36b-opus-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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Darwin-36B-Opus 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.

- Darwin-36B-Opus: C 61, rank #43 of 160 open-weight models · https://www.anchorterminal.com/tools/darwin-36b-opus.min.md
- WeVisOne-VL-4B: C 61, rank #84 of 160 open-weight models · https://www.anchorterminal.com/tools/wevisone-vl-4b.min.md
- Darwin-36B-Opus, good for Reasoning-heavy text tasks on a 32 GB machine or a single 80 GB GPU, where a disclosed training method isn't required Ahead on Reach, 80 against 70; Documentation and upkeep, 61 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 | Darwin-36B-Opus | WeVisOne-VL-4B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 70 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 70 | 70 |
| Documentation and upkeep (10%) | 61 | 48 |

| Fact (where they differ) | Darwin-36B-Opus | WeVisOne-VL-4B |
| --- | --- | --- |
| Vendor | FINAL-Bench (VIDRAFT) | Tencent (WeChat Vision) |
| Last release | 2026-04-23 | 2026-10-27 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Documentation and upkeep, Darwin-36B-Opus +13: Darwin-36B-Opus 61 (Model card 11, it covers architecture, parameters, context and languages but not intended use, limitations or a knowledge cut-off.); WeVisOne-VL-4B 48 (Model card 8, Intended use, limitations and the architecture are on the card.)
- Reach, Darwin-36B-Opus +10: Darwin-36B-Opus 80 (Memory 20, the publisher's Q4_K_M GGUF is 21.2 GB and needs about 25.4 GB with the fifth added, so 32 GB.); 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.)