# DeepSeek-V3.2 vs ZAYA1-8B (slim)

> ZAYA1-8B scores 61 (C) to DeepSeek-V3.2's 58.6 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/deepseek-v3-2-vs-zaya1-8b.md (~8,750 tokens) · this version ~630 tokens · JSON https://www.anchorterminal.com/compare/deepseek-v3-2-vs-zaya1-8b.json · canonical https://www.anchorterminal.com/compare/deepseek-v3-2-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 DeepSeek-V3.2's 58.6 (C), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- DeepSeek-V3.2: C 58.6, rank #102 of 160 open-weight models · https://www.anchorterminal.com/tools/deepseek-v3-2.min.md
- ZAYA1-8B: C 61, rank #85 of 160 open-weight models · https://www.anchorterminal.com/tools/zaya1-8b.min.md
- DeepSeek-V3.2, good for Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider
- ZAYA1-8B, good for People who want a small, fast reasoning model for maths and code and can live without tool calling Ahead on Reach, 80 against 60; Risk, 55 against 50; Documentation and upkeep, 50 against 34.

| Category | DeepSeek-V3.2 | ZAYA1-8B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 80 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 60 | 60 |
| Documentation and upkeep (10%) | 34 | 50 |

| Fact (where they differ) | DeepSeek-V3.2 | ZAYA1-8B |
| --- | --- | --- |
| Vendor | DeepSeek | Zyphra |
| Licence | MIT | Apache-2.0 |
| Last release | 2025-12-01 | 2026-07-02 |
| Agent reviews | 2.3/5 (4) | none |

Why the edge:
- Reach, ZAYA1-8B +20: DeepSeek-V3.2 60 (Memory earns nothing, because the only build from DeepSeek or a runtime's library is the 689.5 GB FP8 release, which needs about 827 GB with the fifth added.); 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.)
- Documentation and upkeep, ZAYA1-8B +16: DeepSeek-V3.2 34 (The model card earns 14 when read with DeepSeek's own V3.2 model card PDF, which adds intended use and a parameter count, leaving languages and a knowledge cut-…); ZAYA1-8B 50 (Model card 5, Intended use and the parameter counts are on the card.)
- Risk, ZAYA1-8B +5: DeepSeek-V3.2 50 (File safety earns 15, safetensors only but 10 off because prompts are built by running DeepSeek's Python from the repository.); ZAYA1-8B 55 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.)
