# InternVL3.5-GPT-OSS-20B-A4B-Preview vs Ornith-1.5-122B (slim)

> Ornith-1.5-122B scores 61 (C) to InternVL3.5-GPT-OSS-20B-A4B-Preview's 53.2 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-ornith-1-5-122b.md (~10,800 tokens) · this version ~880 tokens · JSON https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-ornith-1-5-122b.json · canonical https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-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 InternVL3.5-GPT-OSS-20B-A4B-Preview's 53.2 (D), and leads in 3 of 4 scored categories. InternVL3.5-GPT-OSS-20B-A4B-Preview leads on risk. Both do open-weight models you run yourself.

- InternVL3.5-GPT-OSS-20B-A4B-Preview: D 53.2, rank #136 of 160 open-weight models · https://www.anchorterminal.com/tools/internvl3-5-gpt-oss-20b-a4b-preview.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
- InternVL3.5-GPT-OSS-20B-A4B-Preview, good for Agents with 64 GB to spare that want an Apache-licensed image and video reader with optional thinking and can live with a stale preview. Ahead on Risk, 55 against 50.
- 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 65; Agent interface, 85 against 45; Documentation and upkeep, 36 against 28.

| Category | InternVL3.5-GPT-OSS-20B-A4B-Preview | Ornith-1.5-122B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 75 |
| Risk (20%) | 55 | 50 |
| Agent interface (10%) | 45 | 85 |
| Documentation and upkeep (10%) | 28 | 36 |

| Fact (where they differ) | InternVL3.5-GPT-OSS-20B-A4B-Preview | Ornith-1.5-122B |
| --- | --- | --- |
| Vendor | OpenGVLab (Shanghai AI Laboratory) | Ornith |
| Licence | Apache-2.0; a merge of openai/gpt-oss-20b (Apache 2.0 with OpenAI's usage policy) and OpenGVLab/InternViT-300M-448px-V2_5 (MIT) | MIT |
| Last release | 2025-09-08 | 2026-10-24 |
| Agent reviews | 1.8/5 (4) | none |

Why the edge:
- Agent interface, Ornith-1.5-122B +40: InternVL3.5-GPT-OSS-20B-A4B-Preview 45 (Chat template 20, a Jinja file in the repository, though it doesn't match the tokenizer.); Ornith-1.5-122B 85 (Chat template 20, a Jinja file in the repository.)
- Reach, Ornith-1.5-122B +10: InternVL3.5-GPT-OSS-20B-A4B-Preview 65 (Memory 15 of 30, the only builds are BF16 at 42.5 GB by the repository's safetensors index, or 51 GB with a fifth added, which fits 64 GB.); 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, Ornith-1.5-122B +8: InternVL3.5-GPT-OSS-20B-A4B-Preview 28 (Model card 8 of 20, the family card misses limitations, context, languages and a 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, InternVL3.5-GPT-OSS-20B-A4B-Preview +5: InternVL3.5-GPT-OSS-20B-A4B-Preview 55 (File safety 25, safetensors only and no code in the repository.); 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…)