# Kolibri-1 vs SenseNova-Loop-9B-Preview (slim)

> Kolibri-1 scores 61 (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/kolibri-1-vs-sensenova-loop-9b-preview.md (~10,050 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/kolibri-1-vs-sensenova-loop-9b-preview.json · canonical https://www.anchorterminal.com/compare/kolibri-1-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)

Kolibri-1 scores 61 (C) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in every scored category. Both do open-weight models you run yourself.

- Kolibri-1: C 61, rank #44 of 160 open-weight models · https://www.anchorterminal.com/tools/kolibri-1.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
- Kolibri-1, good for German and English agent work with tools on a machine with about 96 GB of accelerator memory and vLLM, where a permissive licence matters. Ahead on Reach, 65 against 40; Risk, 65 against 50; Agent interface, 90 against 60; Documentation and upkeep, 70 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 | Kolibri-1 | SenseNova-Loop-9B-Preview |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 40 |
| Risk (20%) | 65 | 50 |
| Agent interface (10%) | 90 | 60 |
| Documentation and upkeep (10%) | 70 | 44 |

| Fact (where they differ) | Kolibri-1 | SenseNova-Loop-9B-Preview |
| --- | --- | --- |
| Vendor | Aleph Alpha | SenseTime (SenseNova) |
| Last release | 2026-10-19 | 2026-11-02 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 3.3/5 (4) | none |

Why the edge:
- Agent interface, Kolibri-1 +30: Kolibri-1 90 (The chat template earns 20 as Jinja in tokenizer_config.json.); SenseNova-Loop-9B-Preview 60 (Chat template 20, chat_template.jinja in the repository (7,756 characters).)
- Documentation and upkeep, Kolibri-1 +26: Kolibri-1 70 (The model card earns 20 with all seven items.); 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.)
- Reach, Kolibri-1 +25: Kolibri-1 65 (Memory earns 10 because the smallest qualifying build is Aleph Alpha's own FP8 one at 78.8 GB, which comes to 94.6 GB with the fifth added and so fits only the…); 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…)
- Risk, Kolibri-1 +15: Kolibri-1 65 (File safety earns 25 for safetensors only, with no repository code run on load.); SenseNova-Loop-9B-Preview 50 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)