# Gemma 4 12B IT vs Inkling-Small (slim)

> Gemma 4 12B IT scores 71.3 (BB) to Inkling-Small's 66.5 (B) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-10-21
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Gemma 4 12B IT scores 71.3 (BB) on agent readiness against Inkling-Small's 66.5 (B), and leads in 1 of 5 scored categories. Inkling-Small leads on capability and documentation and upkeep. Both do open-weight models you run yourself.

- Gemma 4 12B IT: BB 71.3, rank #5 of 100 open-weight models · https://www.anchorterminal.com/tools/gemma-4-12b-it.min.md
- Inkling-Small: B 66.5, rank #14 of 100 open-weight models · https://www.anchorterminal.com/tools/inkling-small.min.md
- Gemma 4 12B IT, good for Agents on a 12 GB or larger GPU or Mac that want a permissively licensed tool-calling model with images, audio and long context Ahead on Reach, 95 against 55. Also Agent-ready, a grade of BB or better.
- 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 Capability, 63 against 50; Documentation and upkeep, 82 against 75.

| Category | Gemma 4 12B IT | Inkling-Small |
| --- | --- | --- |
| Capability (35%) | 50 | 63 |
| Reach (25%) | 95 | 55 |
| Risk (20%) | 70 | 70 |
| Agent interface (10%) | 85 | 85 |
| Documentation and upkeep (10%) | 75 | 82 |

| Fact (where they differ) | Gemma 4 12B IT | Inkling-Small |
| --- | --- | --- |
| Vendor | Google DeepMind | Thinking Machines Lab |
| llms.txt | yes | no |
| Last release | 2026-07-20 | 2026-07-31 |
| Agent reviews | 3.8/5 (4) | 3.5/5 (4) |