# DeepSeek-V3.2 vs SenseNova-Loop-9B-Preview (slim)

> DeepSeek-V3.2 scores 58.6 (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/deepseek-v3-2-vs-sensenova-loop-9b-preview.md (~9,500 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/deepseek-v3-2-vs-sensenova-loop-9b-preview.json · canonical https://www.anchorterminal.com/compare/deepseek-v3-2-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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DeepSeek-V3.2 scores 58.6 (C) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 1 of 4 scored categories. SenseNova-Loop-9B-Preview leads on documentation and upkeep. Both do open-weight models you run yourself.

- DeepSeek-V3.2: C 58.6, rank #102 of 160 open-weight models · https://www.anchorterminal.com/tools/deepseek-v3-2.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
- DeepSeek-V3.2, good for Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider Ahead on Reach, 60 against 40.
- 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 34.

| Category | DeepSeek-V3.2 | SenseNova-Loop-9B-Preview |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 40 |
| Risk (20%) | 50 | 50 |
| Agent interface (10%) | 60 | 60 |
| Documentation and upkeep (10%) | 34 | 44 |

| Fact (where they differ) | DeepSeek-V3.2 | SenseNova-Loop-9B-Preview |
| --- | --- | --- |
| Vendor | DeepSeek | SenseTime (SenseNova) |
| Licence | MIT | Apache-2.0 |
| Last release | 2025-12-01 | 2026-11-02 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 2.3/5 (4) | none |

Why the edge:
- Reach, DeepSeek-V3.2 +20: DeepSeek-V3.2 60 (Memory earns nothing, because the only build from DeepSeek or a runtime's library is the 689.5 GB FP8 release, which needs about 827 GB with the 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, SenseNova-Loop-9B-Preview +10: DeepSeek-V3.2 34 (The model card earns 14 when read with DeepSeek's own V3.2 model card PDF, which adds intended use and a parameter count, leaving languages and a knowledge cut-…); 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.)