# Gemma 4 E4B IT vs Ornith-1.5-122B (slim)

> Gemma 4 E4B IT scores 63.2 (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/gemma-4-e4b-it-vs-ornith-1-5-122b.md (~9,350 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-ornith-1-5-122b.json · canonical https://www.anchorterminal.com/compare/gemma-4-e4b-it-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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Gemma 4 E4B IT scores 63.2 (B) on agent readiness against Ornith-1.5-122B's 61 (C), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- Gemma 4 E4B IT: B 63.2, rank #24 of 160 open-weight models · https://www.anchorterminal.com/tools/gemma-4-e4b-it.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
- Gemma 4 E4B IT, good for Agents that need a cheap, permissively licensed helper on 8 GB of memory, for tool calls, short audio or images, rather than hard reasoning Ahead on Reach, 95 against 75; Risk, 70 against 50; Documentation and upkeep, 75 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

| Category | Gemma 4 E4B IT | Ornith-1.5-122B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 95 | 75 |
| Risk (20%) | 70 | 50 |
| Agent interface (10%) | 85 | 85 |
| Documentation and upkeep (10%) | 75 | 36 |

| Fact (where they differ) | Gemma 4 E4B IT | Ornith-1.5-122B |
| --- | --- | --- |
| Vendor | Google DeepMind | Ornith |
| Licence | Apache-2.0 | MIT |
| llms.txt | yes | no |
| Last release | 2026-07-20 | 2026-10-24 |
| Agent reviews | 3.5/5 (4) | none |

Why the edge:
- Documentation and upkeep, Gemma 4 E4B IT +39: Gemma 4 E4B IT 75 (Model card 20, all seven items are there.); 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, Gemma 4 E4B IT +20: Gemma 4 E4B IT 95 (Memory 30, Google's own 4-bit QAT GGUF with its projector is 6.15 GB, which with a fifth on top is 7.4 GB and fits in 16 GB or less.); 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, Gemma 4 E4B IT +20: Gemma 4 E4B IT 70 (File safety 25, safetensors and GGUF only, with nothing from the repository run on load.); 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…)