# Ling-3.0-tiny vs SenseNova-Loop-9B-Preview (slim)

> Ling-3.0-tiny scores 56.2 (C) to SenseNova-Loop-9B-Preview's 46.8 (D) 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-sensenova-loop-9b-preview.md (~9,450 tokens) · this version ~630 tokens · JSON https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-sensenova-loop-9b-preview.json · canonical https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-sensenova-loop-9b-preview
- 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)

Ling-3.0-tiny scores 56.2 (C) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 2 of 4 scored categories. 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
- SenseNova-Loop-9B-Preview: D 46.8, rank #155 of 160 open-weight models · https://www.anchorterminal.com/tools/sensenova-loop-9b-preview.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 40; Documentation and upkeep, 56 against 44.
- SenseNova-Loop-9B-Preview, good for Researchers who want to study or fine-tune a looped transformer, more than agents that need a model to call today

| Category | Ling-3.0-tiny | SenseNova-Loop-9B-Preview |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 95 | 40 |
| Risk (20%) | 50 | 50 |
| Agent interface (10%) | 60 | 60 |
| Documentation and upkeep (10%) | 56 | 44 |

| Fact (where they differ) | Ling-3.0-tiny | SenseNova-Loop-9B-Preview |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | SenseTime (SenseNova) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-08-31 | 2026-11-02 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Reach, Ling-3.0-tiny +55: 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.); SenseNova-Loop-9B-Preview 40 (Memory 15, the only build is the safetensors set, 38.14 GB with its MTP head, since the Hub counts 9.41B of its parameters in F32. Runtimes 0, none of the six r…)
- Documentation and upkeep, Ling-3.0-tiny +12: Ling-3.0-tiny 56 (Model card 11, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't.); SenseNova-Loop-9B-Preview 44 (Model card 14, Intended use, the architecture, the parameter counts, the training context and the languages (in the metadata) are on the card.)