# Hy3 vs Ornith-1.5-122B (slim)

> Hy3 scores 62.6 (B) to Ornith-1.5-122B's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-122b.md (~9,150 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-122b.json · canonical https://www.anchorterminal.com/compare/hy3-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
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Hy3 scores 62.6 (B) on agent readiness against Ornith-1.5-122B's 61 (C), and leads in 2 of 4 scored categories. Ornith-1.5-122B leads on reach and agent interface. Both do open-weight models you run yourself.

- Hy3: B 62.6, rank #28 of 160 open-weight models · https://www.anchorterminal.com/tools/hy3.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
- Hy3, good for Teams with an 8-GPU server who want an agent-tuned MoE model under plain Apache 2.0 Ahead on Risk, 60 against 50; 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 Reach, 75 against 70; Agent interface, 85 against 75.

| Category | Hy3 | Ornith-1.5-122B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 70 | 75 |
| Risk (20%) | 60 | 50 |
| Agent interface (10%) | 75 | 85 |
| Documentation and upkeep (10%) | 56 | 36 |

| Fact (where they differ) | Hy3 | Ornith-1.5-122B |
| --- | --- | --- |
| Vendor | Tencent (Hy team) | Ornith |
| Licence | Apache-2.0 | MIT |
| Last release | 2026-07-20 | 2026-10-24 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Documentation and upkeep, Hy3 +20: Hy3 56 (The model card earns 11, covering intended use, architecture, parameters and context but not 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, Hy3 +10: Hy3 60 (File safety earns the full 25, safetensors only with no pickle files, and the documented route runs vLLM or SGLang from their own code with a Jinja template, so…); 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…)
- Agent interface, Ornith-1.5-122B +10: Hy3 75 (The chat template earns 20, a chat_template.jinja in the repository.); Ornith-1.5-122B 85 (Chat template 20, a Jinja file in the repository.)
- Reach, Ornith-1.5-122B +5: Hy3 70 (Memory earns 5, because the smallest build of 4-bit precision or better is AngelSlim's GPTQ-Int4 of 168.5 GB, about 202 GB with the fifth added, which is within…); 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…)