# DeepSeek V4.1 Flash vs Granite 4.2 30B (slim)

> DeepSeek V4.1 Flash and Granite 4.2 30B score within a point of each other for open-weight models you run yourself, 61.5 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

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DeepSeek V4.1 Flash and Granite 4.2 30B score within a point of each other on agent readiness, 61.5 (C) and 61 (C). Granite 4.2 30B leads on reach, risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- DeepSeek V4.1 Flash: C 61.5, rank #35 of 160 open-weight models · https://www.anchorterminal.com/tools/deepseek-v4-1-flash.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 V4.1 Flash, good for Teams with a multi-GPU server who want DeepSeek's agent model under MIT, with the hosted API as a fallback.
- 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 75; Documentation and upkeep, 87 against 48.

| Category | DeepSeek V4.1 Flash | Granite 4.2 30B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 90 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 75 | 85 |
| Documentation and upkeep (10%) | 48 | 87 |

| Fact (where they differ) | DeepSeek V4.1 Flash | Granite 4.2 30B |
| --- | --- | --- |
| Vendor | DeepSeek | IBM |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-10-17 | 2026-09-04 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Documentation and upkeep, Granite 4.2 30B +39: DeepSeek V4.1 Flash 48 (The cards cover architecture, parameters and context but not intended use, limitations, languages or a cut-off, so 8. Training data is a general description wit…); 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 V4.1 Flash 60 (Memory scores nothing, because the only build is DeepSeek's own at 510.3 GB, about 612 GB with the fifth added, and nobody's runtime library holds a smaller one…); 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 +10: DeepSeek V4.1 Flash 75 (There's no Jinja template in the 17 October repository, only code to run, so the template line gets 10. DeepSeek documents the DSML tool format both ways and sh…); 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 V4.1 Flash 50 (The weights are safetensors only, but 10 comes off because the card's way to build prompts is running encoding.py from the repository, since there's no Jinja te…); Granite 4.2 30B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)