# Agents-A1-4B vs North Mini Code 1.0 (slim)

> Agents-A1-4B and North Mini Code 1.0 score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. 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: 2026-11-10
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Agents-A1-4B and North Mini Code 1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). North Mini Code 1.0 leads on risk and agent interface. Both do open-weight models you run yourself.

- Agents-A1-4B: C 61, rank #39 of 160 open-weight models · https://www.anchorterminal.com/tools/agents-a1-4b.min.md
- North Mini Code 1.0: C 61, rank #80 of 160 open-weight models · https://www.anchorterminal.com/tools/north-mini-code-1-0.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 85; Documentation and upkeep, 43 against 36.
- North Mini Code 1.0, good for Developers who want a coding agent on their own GPU with a permissive licence Ahead on Risk, 60 against 55; Agent interface, 85 against 70.

| Category | Agents-A1-4B | North Mini Code 1.0 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 85 |
| Risk (20%) | 55 | 60 |
| Agent interface (10%) | 70 | 85 |
| Documentation and upkeep (10%) | 43 | 36 |

| Fact (where they differ) | Agents-A1-4B | North Mini Code 1.0 |
| --- | --- | --- |
| Vendor | InternScience (Shanghai AI Laboratory) | Cohere |
| Last release | 2026-07-14 | 2026-07-29 |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Agent interface, North Mini Code 1.0 +15: Agents-A1-4B 70 (Chat template 20, a Jinja file in the repository.); North Mini Code 1.0 85 (Chat template 20, chat_template.jinja in the repository (12,397 characters).)
- Documentation and upkeep, Agents-A1-4B +7: Agents-A1-4B 43 (Model card 8, it covers intended use, parameters and context but not the architecture, limitations, languages or a knowledge cut-off.); North Mini Code 1.0 36 (Model card 11, Intended use, the architecture, the parameters and the context are on the card.)
- Reach, Agents-A1-4B +5: Agents-A1-4B 90 (Memory 30, InternScience's Q4_K_M GGUF with its vision projector is 3.4 GB and needs about 4.1 GB with the fifth added.); North Mini Code 1.0 85 (Memory 25, the smallest build from Cohere is the w4a16 repository, 19.38 GB, and 19.38 GB × 1.2 = 23.3 GB, within 24 GB.)
- Risk, North Mini Code 1.0 +5: Agents-A1-4B 55 (File safety 25, safetensors and GGUF only and nothing from the repository runs.); North Mini Code 1.0 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.)