# Agents-A1-4B vs Ornith-1.5-122B (slim)

> Agents-A1-4B and Ornith-1.5-122B 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 Ornith-1.5-122B score within a point of each other on agent readiness, 61 (C) and 61 (C). Ornith-1.5-122B leads on 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
- Ornith-1.5-122B: C 61, rank #81 of 160 open-weight models · https://www.anchorterminal.com/tools/ornith-1-5-122b.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 75; Risk, 55 against 50; Documentation and upkeep, 43 against 36.
- Ornith-1.5-122B, good for Local coding and terminal agents on a 128 GB unified-memory machine or a 96 GB GPU setup, where a clear licence file and an answering publisher aren't required Ahead on Agent interface, 85 against 70.

| Category | Agents-A1-4B | Ornith-1.5-122B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 75 |
| Risk (20%) | 55 | 50 |
| Agent interface (10%) | 70 | 85 |
| Documentation and upkeep (10%) | 43 | 36 |

| Fact (where they differ) | Agents-A1-4B | Ornith-1.5-122B |
| --- | --- | --- |
| Vendor | InternScience (Shanghai AI Laboratory) | Ornith |
| Licence | Apache-2.0 | MIT |
| Last release | 2026-07-14 | 2026-10-24 |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Reach, Agents-A1-4B +15: 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.); Ornith-1.5-122B 75 (Memory 10, since Ornith's own MLX 4-bit build is 69.7 GB and needs about 83.6 GB with the fifth added, over 64 GB and inside the reference machine's 107.4 GB, a…)
- Agent interface, Ornith-1.5-122B +15: Agents-A1-4B 70 (Chat template 20, a Jinja file in the repository.); Ornith-1.5-122B 85 (Chat template 20, a Jinja file in the repository.)
- 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.); Ornith-1.5-122B 36 (Model card 11, it covers intended use, architecture, parameters and context but not limitations, languages or a knowledge cut-off.)
- Risk, Agents-A1-4B +5: Agents-A1-4B 55 (File safety 25, safetensors and GGUF only and nothing from the repository runs.); Ornith-1.5-122B 50 (File safety 25, safetensors and GGUF only and no Python in any of Ornith's repositories for this size, so the card's --trust-remote-code flag loads nothing from…)