# Qwen3-VL-4B-Instruct vs ZAYA1-8B (slim)

> ZAYA1-8B scores 61 (C) to Qwen3-VL-4B-Instruct's 52.6 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-zaya1-8b.md (~8,700 tokens) · this version ~530 tokens · JSON https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-zaya1-8b.json · canonical https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-zaya1-8b
- 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
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

ZAYA1-8B scores 61 (C) on agent readiness against Qwen3-VL-4B-Instruct's 52.6 (D), and leads in 1 of 4 scored categories. Qwen3-VL-4B-Instruct leads on reach. Both do open-weight models you run yourself.

- Qwen3-VL-4B-Instruct: D 52.6, rank #137 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-vl-4b-instruct.min.md
- ZAYA1-8B: C 61, rank #85 of 160 open-weight models · https://www.anchorterminal.com/tools/zaya1-8b.min.md
- Qwen3-VL-4B-Instruct, good for An agent with 4 GB or more to spare that needs a local model to read images, documents and video Ahead on Reach, 95 against 80.
- ZAYA1-8B, good for People who want a small, fast reasoning model for maths and code and can live without tool calling Ahead on Documentation and upkeep, 50 against 31.

| Category | Qwen3-VL-4B-Instruct | ZAYA1-8B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 95 | 80 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 60 | 60 |
| Documentation and upkeep (10%) | 31 | 50 |

| Fact (where they differ) | Qwen3-VL-4B-Instruct | ZAYA1-8B |
| --- | --- | --- |
| Vendor | Alibaba (Qwen team) | Zyphra |
| Last release | 2025-11-01 | 2026-07-02 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Documentation and upkeep, ZAYA1-8B +19: Qwen3-VL-4B-Instruct 31 (The card misses limitations, languages and a cut-off (11).); ZAYA1-8B 50 (Model card 5, Intended use and the parameter counts are on the card.)
- Reach, Qwen3-VL-4B-Instruct +15: Qwen3-VL-4B-Instruct 95 (Alibaba's own Q4_K_M GGUF with its vision file is 2.95 GB, so with a fifth added it needs about 3.5 GB and fits well within 16 GB (30).); ZAYA1-8B 80 (Memory 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB.)