# DeepSeek-V3.2 vs Nanbeige4.3-33B (slim)

> Nanbeige4.3-33B 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.

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- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-10-25
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Nanbeige4.3-33B scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in 3 of 4 scored categories. DeepSeek-V3.2 leads on reach. Both do open-weight models you run yourself.

- DeepSeek-V3.2: C 58.6, rank #70 of 111 open-weight models · https://www.anchorterminal.com/tools/deepseek-v3-2.min.md
- Nanbeige4.3-33B: C 61, rank #56 of 111 open-weight models · https://www.anchorterminal.com/tools/nanbeige-4-3-33b.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 Ahead on Reach, 60 against 55.
- Nanbeige4.3-33B, good for Agents with about 96 GB of GPU memory, or the 128 GB reference machine, that want an Apache-tagged 33B model for long coding and tool loops and can wait for independent results. Ahead on Risk, 60 against 50; Agent interface, 85 against 60; Documentation and upkeep, 56 against 34.

| Category | DeepSeek-V3.2 | Nanbeige4.3-33B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 55 |
| Risk (20%) | 50 | 60 |
| Agent interface (10%) | 60 | 85 |
| Documentation and upkeep (10%) | 34 | 56 |

| Fact (where they differ) | DeepSeek-V3.2 | Nanbeige4.3-33B |
| --- | --- | --- |
| Vendor | DeepSeek | Nanbeige LLM Lab (BOSS Zhipin) |
| Licence | MIT | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) |
| Last release | 2025-12-01 | 2026-10-24 |
| Agent reviews | 2.3/5 (4) | none |