# Nemotron 3 Nano 4B vs Ornith-1.5-122B (slim)

> Ornith-1.5-122B scores 61 (C) to Nemotron 3 Nano 4B's 56.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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Ornith-1.5-122B scores 61 (C) on agent readiness against Nemotron 3 Nano 4B's 56.8 (C), and leads in 1 of 4 scored categories. Nemotron 3 Nano 4B leads on reach, risk and documentation and upkeep. Both do open-weight models you run yourself.

- Nemotron 3 Nano 4B: C 56.8, rank #110 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-nano-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
- Nemotron 3 Nano 4B, good for Agents on laptops, edge boards and small GPUs that need a cheap local tool-calling helper in English Ahead on Reach, 90 against 75; Risk, 65 against 50; Documentation and upkeep, 55 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 | Nemotron 3 Nano 4B | Ornith-1.5-122B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 75 |
| Risk (20%) | 65 | 50 |
| Agent interface (10%) | 70 | 85 |
| Documentation and upkeep (10%) | 55 | 36 |

| Fact (where they differ) | Nemotron 3 Nano 4B | Ornith-1.5-122B |
| --- | --- | --- |
| Vendor | NVIDIA | Ornith |
| Licence | NVIDIA Nemotron Open Model License | MIT |
| Last release | 2026-03-16 | 2026-10-24 |
| Agent reviews | 3.3/5 (4) | none |

Why the edge:
- Documentation and upkeep, Nemotron 3 Nano 4B +19: Nemotron 3 Nano 4B 55 (The model card earns 20, all seven items with limitations in the linked subcard.); 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.)
- Reach, Nemotron 3 Nano 4B +15: Nemotron 3 Nano 4B 90 (Memory earns the full 30, since NVIDIA's own 2.84 GB GGUF needs under 4 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…)
- Risk, Nemotron 3 Nano 4B +15: Nemotron 3 Nano 4B 65 (File safety earns 15, safetensors and GGUF only but with 10 off because the documented commands pass trust_remote_code and load a parser plugin from the reposit…); 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 +15: Nemotron 3 Nano 4B 70 (The chat template earns 20, a Jinja file in the repository.); Ornith-1.5-122B 85 (Chat template 20, a Jinja file in the repository.)