# GLM-4.7-Flash vs SenseNova-Loop-9B-Preview (slim)

> GLM-4.7-Flash scores 63 (B) 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/glm-4-7-flash-vs-sensenova-loop-9b-preview.md (~10,050 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/glm-4-7-flash-vs-sensenova-loop-9b-preview.json · canonical https://www.anchorterminal.com/compare/glm-4-7-flash-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
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GLM-4.7-Flash scores 63 (B) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 3 of 4 scored categories. SenseNova-Loop-9B-Preview leads on documentation and upkeep. Both do open-weight models you run yourself.

- GLM-4.7-Flash: B 63, rank #26 of 160 open-weight models · https://www.anchorterminal.com/tools/glm-4-7-flash.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
- GLM-4.7-Flash, good for Agents and developers who want a small, permissively licensed tool-calling model on one 24 to 32 GB GPU or Mac, in almost any runtime Ahead on Reach, 80 against 40; Risk, 55 against 50; Agent interface, 85 against 60.
- 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 Ahead on Documentation and upkeep, 44 against 28.

| Category | GLM-4.7-Flash | SenseNova-Loop-9B-Preview |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 40 |
| Risk (20%) | 55 | 50 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 28 | 44 |

| Fact (where they differ) | GLM-4.7-Flash | SenseNova-Loop-9B-Preview |
| --- | --- | --- |
| Vendor | Z.ai (Zhipu AI) | SenseTime (SenseNova) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-01-29 | 2026-11-02 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Reach, GLM-4.7-Flash +40: GLM-4.7-Flash 80 (Memory earns 25, since Ollama's smallest build is the 19 GB q4_K_M one, about 22.8 GB with the fifth added, which fits 24 GB.); 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…)
- Agent interface, GLM-4.7-Flash +25: GLM-4.7-Flash 85 (A Jinja chat template sits in the repository, for 20. The tool-calling format is the full 25, because Z.ai itself names the glm47 parser for vLLM and SGLang, sa…); SenseNova-Loop-9B-Preview 60 (Chat template 20, chat_template.jinja in the repository (7,756 characters).)
- Documentation and upkeep, SenseNova-Loop-9B-Preview +16: GLM-4.7-Flash 28 (The card covers architecture, parameters and languages and misses four of the seven items, for 8. Training data is 0, as the card describes none.); 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.)
- Risk, GLM-4.7-Flash +5: GLM-4.7-Flash 55 (File safety is full, with safetensors only and the card loading it through Transformers' own code without remote code.); SenseNova-Loop-9B-Preview 50 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)