# Inkling-Small vs LongCat-2.5 (slim)

> Inkling-Small scores 67 (B) to LongCat-2.5's 50.5 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/inkling-small-vs-longcat-2-5.md (~9,500 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/inkling-small-vs-longcat-2-5.json · canonical https://www.anchorterminal.com/compare/inkling-small-vs-longcat-2-5
- 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)

Inkling-Small scores 67 (B) on agent readiness against LongCat-2.5's 50.5 (D), and leads in every scored category. Both do open-weight models you run yourself.

- Inkling-Small: B 67, rank #13 of 160 open-weight models · https://www.anchorterminal.com/tools/inkling-small.min.md
- LongCat-2.5: D 50.5, rank #145 of 160 open-weight models · https://www.anchorterminal.com/tools/longcat-2-5.min.md
- Inkling-Small, good for Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking. Ahead on Reach, 55 against 35; Risk, 70 against 60; Agent interface, 85 against 75; Documentation and upkeep, 87 against 46.
- LongCat-2.5, good for Operators with NPU clusters, and anyone tracking what the open flagships can do

| Category | Inkling-Small | LongCat-2.5 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 55 | 35 |
| Risk (20%) | 70 | 60 |
| Agent interface (10%) | 85 | 75 |
| Documentation and upkeep (10%) | 87 | 46 |

| Fact (where they differ) | Inkling-Small | LongCat-2.5 |
| --- | --- | --- |
| Vendor | Thinking Machines Lab | Meituan (LongCat) |
| Licence | Apache-2.0 | MIT |
| Last release | 2026-07-31 | 2026-11-10 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 3.5/5 (4) | none |

Why the edge:
- Documentation and upkeep, Inkling-Small +41: Inkling-Small 87 (Model card 17 of 20, everything but a dated knowledge cut-off, counting Thinking Machines' own model card page.); LongCat-2.5 46 (Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card.)
- Reach, Inkling-Small +20: Inkling-Small 55 (Memory 5 of 30, the smallest 4-bit build is Thinking Machines' NVFP4 at 170.8 GB, about 205 GB with a fifth added, so it needs 256 GB.); LongCat-2.5 35 (Memory 0, the smallest build is Meituan's W4A4 repository, 1,336 GB, and 1,336 GB × 1.2 = 1,603 GB, far above 256 GB.)
- Risk, Inkling-Small +10: Inkling-Small 70 (File safety 25, safetensors only and no repository code to run.); LongCat-2.5 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.)
- Agent interface, Inkling-Small +10: Inkling-Small 85 (Chat template 20, a Jinja file in the repository.); LongCat-2.5 75 (Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json.)