# Gemma 4 E2B IT vs Nanbeige4.2-3B (slim)

> Nanbeige4.2-3B and Gemma 4 E2B IT score within a point of each other for open-weight models you run yourself, 61 and 60.4 out of 100. 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: 2026-11-10
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Nanbeige4.2-3B and Gemma 4 E2B IT score within a point of each other on agent readiness, 61 (C) and 60.4 (C). Gemma 4 E2B IT leads on reach and risk. Both do open-weight models you run yourself.

- Gemma 4 E2B IT: C 60.4, rank #88 of 160 open-weight models · https://www.anchorterminal.com/tools/gemma-4-e2b-it.min.md
- Nanbeige4.2-3B: C 61, rank #78 of 160 open-weight models · https://www.anchorterminal.com/tools/nanbeige-4-2-3b.min.md
- Gemma 4 E2B IT, good for Agents that need a cheap, permissively licensed helper on 8 GB of memory, for tool calls, short audio or images, rather than hard reasoning Ahead on Reach, 95 against 85; Risk, 70 against 55.
- Nanbeige4.2-3B, good for Local agents that need tool calling and a long context on a laptop or a small GPU

| Category | Gemma 4 E2B IT | Nanbeige4.2-3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 95 | 85 |
| Risk (20%) | 70 | 55 |
| Agent interface (10%) | 85 | 85 |
| Documentation and upkeep (10%) | 75 | 72 |

| Fact (where they differ) | Gemma 4 E2B IT | Nanbeige4.2-3B |
| --- | --- | --- |
| Vendor | Google DeepMind | Nanbeige LLM Lab (BOSS Zhipin) |
| Licence | Apache-2.0 | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) |
| llms.txt | yes | no |
| Last release | 2026-11-03 | 2026-09-11 |
| Agent reviews | 3.5/5 (4) | none |

Why the edge:
- Risk, Gemma 4 E2B IT +15: Gemma 4 E2B IT 70 (File safety 25, safetensors and GGUF only, with nothing from the repository run on load.); Nanbeige4.2-3B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Reach, Gemma 4 E2B IT +10: Gemma 4 E2B IT 95 (Memory 30, Google's own 4-bit QAT GGUF with its projector is 4.34 GB, which with a fifth on top is 5.2 GB and fits in 16 GB or less.); Nanbeige4.2-3B 85 (Memory 30, the smallest build from Nanbeige is the FP8 repository (the 8-bit GPTQ one is the same size), 5.19 GB, and 5.19 GB × 1.2 = 6.2 GB, within 16 GB.)