# DeepSeek-V3.2 vs Granite 4.2 30B (slim)

> Granite 4.2 30B scores 61 (C) to DeepSeek-V3.2's 58.6 (C) 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 DeepSeek-V3.2's 58.6 (C), and leads in every scored category. Both do open-weight models you run yourself.

- DeepSeek-V3.2: C 58.6, rank #102 of 160 open-weight models · https://www.anchorterminal.com/tools/deepseek-v3-2.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
- DeepSeek-V3.2, good for Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider
- 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 60; Risk, 55 against 50; Agent interface, 85 against 60; Documentation and upkeep, 87 against 34.

| Category | DeepSeek-V3.2 | Granite 4.2 30B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 90 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 60 | 85 |
| Documentation and upkeep (10%) | 34 | 87 |

| Fact (where they differ) | DeepSeek-V3.2 | Granite 4.2 30B |
| --- | --- | --- |
| Vendor | DeepSeek | IBM |
| Licence | MIT | Apache-2.0 |
| Last release | 2025-12-01 | 2026-09-04 |
| Agent reviews | 2.3/5 (4) | none |

Why the edge:
- Documentation and upkeep, Granite 4.2 30B +53: DeepSeek-V3.2 34 (The model card earns 14 when read with DeepSeek's own V3.2 model card PDF, which adds intended use and a parameter count, leaving languages and a knowledge cut-…); 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…)
- Reach, Granite 4.2 30B +30: DeepSeek-V3.2 60 (Memory earns nothing, because the only build from DeepSeek or a runtime's library is the 689.5 GB FP8 release, which needs about 827 GB with the fifth added.); 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.)
- Agent interface, Granite 4.2 30B +25: DeepSeek-V3.2 60 (The chat template earns 10, as the format exists only as Python code to run.); 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.)
- Risk, Granite 4.2 30B +5: DeepSeek-V3.2 50 (File safety earns 15, safetensors only but 10 off because prompts are built by running DeepSeek's Python from the repository.); Granite 4.2 30B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)