# DiffusionGemma 26B A4B IT vs Granite 4.2 30B (slim)

> Granite 4.2 30B 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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Granite 4.2 30B 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
- Granite 4.2 30B: C 61, rank #65 of 160 open-weight models · https://www.anchorterminal.com/tools/granite-4-2-30b.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.
- Granite 4.2 30B, good for Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 24 GB card Ahead on Reach, 90 against 55; Agent interface, 85 against 70; Documentation and upkeep, 87 against 60.

| Category | DiffusionGemma 26B A4B IT | Granite 4.2 30B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 55 | 90 |
| Risk (20%) | 70 | 55 |
| Agent interface (10%) | 70 | 85 |
| Documentation and upkeep (10%) | 60 | 87 |

| Fact (where they differ) | DiffusionGemma 26B A4B IT | Granite 4.2 30B |
| --- | --- | --- |
| Vendor | Google DeepMind | IBM |
| llms.txt | yes | no |
| Last release | 2026-07-15 | 2026-09-04 |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Reach, Granite 4.2 30B +35: 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.); Granite 4.2 30B 90 (Memory 25, IBM's own 4-bit MLX build granite-4.2-30b-q4-mlx is 16.47 GB, and 16.47 GB × 1.2 = 19.8 GB, which fits 24 GB but not 16 GB.)
- Documentation and upkeep, Granite 4.2 30B +27: 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).); Granite 4.2 30B 87 (Model card 17, Intended use (best for), limitations (ethical considerations and limitations), architecture, parameters (30B), context length (128K native) and 1…)
- 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.); Granite 4.2 30B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Agent interface, Granite 4.2 30B +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).); Granite 4.2 30B 85 (Chat template 20, chat_template.jinja in the repository, with roles, tools, tool responses, the thinking switch and low effort.)