# Granite 4.2 30B vs Kimi K3 (slim)

> Kimi K3 scores 62.4 (B) to Granite 4.2 30B's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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Kimi K3 scores 62.4 (B) on agent readiness against Granite 4.2 30B's 61 (C), and leads in 1 of 4 scored categories. Granite 4.2 30B leads on reach, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- Granite 4.2 30B: C 61, rank #65 of 160 open-weight models · https://www.anchorterminal.com/tools/granite-4-2-30b.min.md
- Kimi K3: B 62.4, rank #30 of 160 open-weight models · https://www.anchorterminal.com/tools/kimi-k3.min.md
- 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 50; Agent interface, 85 against 65; Documentation and upkeep, 87 against 41.
- Kimi K3, good for Teams with a multi-node GPU cluster who want an open 1M-context agent model for long coding and research work Ahead on Risk, 65 against 55.

| Category | Granite 4.2 30B | Kimi K3 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 50 |
| Risk (20%) | 55 | 65 |
| Agent interface (10%) | 85 | 65 |
| Documentation and upkeep (10%) | 87 | 41 |

| Fact (where they differ) | Granite 4.2 30B | Kimi K3 |
| --- | --- | --- |
| Vendor | IBM | Moonshot AI |
| Licence | Apache-2.0 | Kimi K3 License (modified MIT) |
| Last release | 2026-09-04 | 2026-09-02 |
| Agent reviews | none | 2.3/5 (4) |

Why the edge:
- Documentation and upkeep, Granite 4.2 30B +46: 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…); Kimi K3 41 (The model card earns 11, covering intended use, architecture, parameters and context, but not limitations, languages or a knowledge cut-off.)
- Reach, Granite 4.2 30B +40: 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.); Kimi K3 50 (Memory earns nothing, because the only build of 4-bit precision or better from Moonshot or a runtime's own library is Moonshot's MXFP4 release of 1,561 GB, abou…)
- Agent interface, Granite 4.2 30B +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.); Kimi K3 65 (The chat template earns 10, because there is no Jinja template and the prompt format exists only as encoding_k3.py, code you run.)
- Risk, Kimi K3 +10: Granite 4.2 30B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Kimi K3 65 (File safety earns 15, safetensors only with no pickle files, less 10 because the documented loading path runs Moonshot's Python with trust_remote_code and build…)