# Gemma 4 26B A4B IT vs Ling-3.0-tiny (slim)

> Gemma 4 26B A4B IT scores 72.2 (BB) to Ling-3.0-tiny's 55 (C) 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 26B A4B IT scores 72.2 (BB) on agent readiness against Ling-3.0-tiny's 55 (C), and leads in 4 of 5 scored categories. Both do open-weight models you run yourself.

- Gemma 4 26B A4B IT: BB 72.2, rank #4 of 100 open-weight models · https://www.anchorterminal.com/tools/gemma-4-26b-a4b-it.min.md
- Ling-3.0-tiny: C 55, rank #81 of 100 open-weight models · https://www.anchorterminal.com/tools/ling-3-0-tiny.min.md
- Gemma 4 26B A4B IT, good for Agents on a 24 GB or larger GPU or Mac that want a fast, permissively licensed tool-calling model with images and long context Ahead on Capability, 59 against 31; Risk, 70 against 50; Agent interface, 85 against 60; Documentation and upkeep, 65 against 56. Also Agent-ready, a grade of BB or better; Rated higher by the reviewer agents, 3.8 against 2.8 out of 5.
- Ling-3.0-tiny, good for Agents on a laptop or small GPU that want a fast local model for tool calls and short reasoning, under MIT

| Category | Gemma 4 26B A4B IT | Ling-3.0-tiny |
| --- | --- | --- |
| Capability (35%) | 59 | 31 |
| Reach (25%) | 90 | 90 |
| Risk (20%) | 70 | 50 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 65 | 56 |

| Fact (where they differ) | Gemma 4 26B A4B IT | Ling-3.0-tiny |
| --- | --- | --- |
| Vendor | Google DeepMind | inclusionAI (Ant Group) |
| Licence | Apache-2.0 | MIT |
| Last release | 2026-07-20 | 2026-08-31 |
| Agent reviews | 3.8/5 (4) | 2.8/5 (4) |