# Ling-3.0-tiny vs Ornith-1.5-122B (slim)

> Ornith-1.5-122B scores 61 (C) to Ling-3.0-tiny's 56.2 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-122b.md (~9,300 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-122b.json · canonical https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-122b
- 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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Ornith-1.5-122B scores 61 (C) on agent readiness against Ling-3.0-tiny's 56.2 (C), and leads in 1 of 4 scored categories. Ling-3.0-tiny leads on reach and documentation and upkeep. Both do open-weight models you run yourself.

- Ling-3.0-tiny: C 56.2, rank #117 of 160 open-weight models · https://www.anchorterminal.com/tools/ling-3-0-tiny.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
- Ling-3.0-tiny, good for Agents on a laptop or small GPU that want a fast local model for tool calls and short reasoning, under MIT Ahead on Reach, 95 against 75; Documentation and upkeep, 56 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 60.

| Category | Ling-3.0-tiny | Ornith-1.5-122B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 95 | 75 |
| Risk (20%) | 50 | 50 |
| Agent interface (10%) | 60 | 85 |
| Documentation and upkeep (10%) | 56 | 36 |

| Fact (where they differ) | Ling-3.0-tiny | Ornith-1.5-122B |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | Ornith |
| Last release | 2026-08-31 | 2026-10-24 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Agent interface, Ornith-1.5-122B +25: Ling-3.0-tiny 60 (Chat template 20, a Jinja file in the repository.); Ornith-1.5-122B 85 (Chat template 20, a Jinja file in the repository.)
- Reach, Ling-3.0-tiny +20: Ling-3.0-tiny 95 (Memory earns the full 30, since inclusionAI's own Q4_K_M GGUF is 4.8 GB, about 6 GB with a 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…)
- Documentation and upkeep, Ling-3.0-tiny +20: Ling-3.0-tiny 56 (Model card 11, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't.); 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.)