# GLM-5.3 vs SenseNova-Loop-9B-Preview (slim)

> GLM-5.3 scores 64.6 (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-5-3-vs-sensenova-loop-9b-preview.md (~9,450 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/glm-5-3-vs-sensenova-loop-9b-preview.json · canonical https://www.anchorterminal.com/compare/glm-5-3-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: 2026-11-11
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

GLM-5.3 scores 64.6 (B) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- GLM-5.3: B 64.6, rank #21 of 160 open-weight models · https://www.anchorterminal.com/tools/glm-5-3.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-5.3, good for Teams with an 8-GPU server who want an open coding and long-horizon agent model with a 1M-token context, or agents that call it through Z.ai or a hosted provider Ahead on Reach, 55 against 40; Agent interface, 70 against 60; Documentation and upkeep, 58 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 | GLM-5.3 | SenseNova-Loop-9B-Preview |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 55 | 40 |
| Risk (20%) | 50 | 50 |
| Agent interface (10%) | 70 | 60 |
| Documentation and upkeep (10%) | 58 | 44 |

| Fact (where they differ) | GLM-5.3 | SenseNova-Loop-9B-Preview |
| --- | --- | --- |
| Vendor | Z.ai (Zhipu AI) | SenseTime (SenseNova) |
| Licence | GLM-5.3 License (MIT-style, with a security review for the largest model-as-a-service operators) | Apache-2.0 |
| Last release | 2026-10-15 | 2026-11-02 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Reach, GLM-5.3 +15: GLM-5.3 55 (Memory earns nothing, since Z.ai's smallest build is the 755.6 GB FP8 one, about 907 GB with the fifth added, and Ollama only lists a cloud entry.); 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, GLM-5.3 +14: GLM-5.3 58 (The card covers intended use, languages and context and misses limitations, architecture, parameters and cut-off, for 8. Training data is 5, a description of th…); 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.)
- Agent interface, GLM-5.3 +10: GLM-5.3 70 (A Jinja chat template sits in the repository, for 20. The tool-calling format is 10, since it is defined only by the template and the glm47 parser is named by v…); SenseNova-Loop-9B-Preview 60 (Chat template 20, chat_template.jinja in the repository (7,756 characters).)