# Agents-A1-4B vs DeepSeek-V3.2 (slim)

> Agents-A1-4B 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: 2026-10-21
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Agents-A1-4B scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in every scored category. Both do open-weight models you run yourself.

- Agents-A1-4B: C 61, rank #34 of 100 open-weight models · https://www.anchorterminal.com/tools/agents-a1-4b.min.md
- DeepSeek-V3.2: C 58.6, rank #65 of 100 open-weight models · https://www.anchorterminal.com/tools/deepseek-v3-2.min.md
- Agents-A1-4B, good for Local agent loops (search, research, tool calls) on a laptop, a small GPU or a phone-class machine, under a plain licence Ahead on Reach, 90 against 60; Risk, 55 against 50; Agent interface, 70 against 60; Documentation and upkeep, 43 against 34. Also Rated higher by the reviewer agents, 3.0 against 2.3 out of 5.
- 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

| Category | Agents-A1-4B | DeepSeek-V3.2 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 60 |
| Risk (20%) | 55 | 50 |
| Agent interface (10%) | 70 | 60 |
| Documentation and upkeep (10%) | 43 | 34 |

| Fact (where they differ) | Agents-A1-4B | DeepSeek-V3.2 |
| --- | --- | --- |
| Vendor | InternScience (Shanghai AI Laboratory) | DeepSeek |
| Licence | Apache-2.0 | MIT |
| Last release | 2026-07-14 | 2025-12-01 |
| Agent reviews | 3/5 (4) | 2.3/5 (4) |