# DiffusionGemma 26B A4B IT vs Nanbeige4.2-3B (slim)

> Nanbeige4.2-3B scores 61 (C) to DiffusionGemma 26B A4B IT's 51.3 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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Nanbeige4.2-3B scores 61 (C) on agent readiness against DiffusionGemma 26B A4B IT's 51.3 (D), and leads in 3 of 4 scored categories. DiffusionGemma 26B A4B IT leads on risk. Both do open-weight models you run yourself.

- DiffusionGemma 26B A4B IT: D 51.3, rank #143 of 160 open-weight models · https://www.anchorterminal.com/tools/diffusiongemma-26b-a4b-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
- DiffusionGemma 26B A4B IT, good for Agents with about 64 GB of GPU memory that want fast single-user generation from text and images and can accept lower quality than Gemma 4 Ahead on 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 Ahead on Reach, 85 against 55; Agent interface, 85 against 70; Documentation and upkeep, 72 against 60.

| Category | DiffusionGemma 26B A4B IT | Nanbeige4.2-3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 55 | 85 |
| Risk (20%) | 70 | 55 |
| Agent interface (10%) | 70 | 85 |
| Documentation and upkeep (10%) | 60 | 72 |

| Fact (where they differ) | DiffusionGemma 26B A4B 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 | 2026-07-15 | 2026-09-11 |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Reach, Nanbeige4.2-3B +30: DiffusionGemma 26B A4B IT 55 (Memory earns 15 because the only Google build is 51.7 GB of BF16, about 62 GB with the fifth added, which needs the 64 GB band.); 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.)
- Risk, DiffusionGemma 26B A4B IT +15: DiffusionGemma 26B A4B IT 70 (File safety gets the full 25, safetensors only and loaded by Transformers' own code and a Jinja template.); Nanbeige4.2-3B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Agent interface, Nanbeige4.2-3B +15: DiffusionGemma 26B A4B IT 70 (The chat template is in the repository (20) and handles several tool calls in one turn, and the card names function calling as trained (20).); Nanbeige4.2-3B 85 (Chat template 20, A Jinja chat template in tokenizer_config.json (7,961 characters), with enable_thinking, preserve_thinking, tools and tool_call_format switche…)
- Documentation and upkeep, Nanbeige4.2-3B +12: DiffusionGemma 26B A4B IT 60 (The card covers all seven points (20), and the training data is a general description with a January 2025 cut-off (10).); Nanbeige4.2-3B 72 (Model card 17, Intended use, limitations, the architecture, the parameters (3B outside the embeddings), the context and the languages (in the metadata) are on t…)