# Qwen3.5-4B vs ZAYA1-8B (slim)

> Qwen3.5-4B and ZAYA1-8B 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-zaya1-8b.md (~8,450 tokens) · this version ~630 tokens · JSON https://www.anchorterminal.com/compare/qwen3-5-4b-vs-zaya1-8b.json · canonical https://www.anchorterminal.com/compare/qwen3-5-4b-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
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Qwen3.5-4B and ZAYA1-8B score within a point of each other on agent readiness, 61.2 (C) and 61 (C). ZAYA1-8B 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
- ZAYA1-8B: C 61, rank #85 of 160 open-weight models · https://www.anchorterminal.com/tools/zaya1-8b.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 80; Agent interface, 70 against 60.
- 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 34.

| Category | Qwen3.5-4B | ZAYA1-8B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 80 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 70 | 60 |
| Documentation and upkeep (10%) | 34 | 50 |

| Fact (where they differ) | Qwen3.5-4B | ZAYA1-8B |
| --- | --- | --- |
| Vendor | Alibaba (Qwen team) | Zyphra |
| Last release | 2026-03-02 | 2026-07-02 |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Documentation and upkeep, ZAYA1-8B +16: Qwen3.5-4B 34 (The card covers five of the seven items and misses limitations and a cut-off (14).); ZAYA1-8B 50 (Model card 5, Intended use and the parameter counts are on the card.)
- Agent interface, Qwen3.5-4B +10: Qwen3.5-4B 70 (The template ships in the repository (20) and the model was trained for tool use with several calls per turn in the template (20).); ZAYA1-8B 60 (Chat template 20, chat_template.jinja in the repository (10,700 characters).)
- Reach, Qwen3.5-4B +5: 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…); 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.)