# EXAONE 4.5 33B vs Kimi K3 (slim)

> Kimi K3 scores 62.4 (B) to EXAONE 4.5 33B'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 EXAONE 4.5 33B's 61 (C), and leads in 1 of 4 scored categories. EXAONE 4.5 33B leads on reach, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- EXAONE 4.5 33B: C 61, rank #61 of 160 open-weight models · https://www.anchorterminal.com/tools/exaone-4-5-33b.min.md
- Kimi K3: B 62.4, rank #30 of 160 open-weight models · https://www.anchorterminal.com/tools/kimi-k3.min.md
- EXAONE 4.5 33B, good for Researchers and students working on documents, Korean or multimodal agents who don't need commercial rights Ahead on Reach, 65 against 50; Agent interface, 85 against 65; Documentation and upkeep, 50 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 50.

| Category | EXAONE 4.5 33B | Kimi K3 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 50 |
| Risk (20%) | 50 | 65 |
| Agent interface (10%) | 85 | 65 |
| Documentation and upkeep (10%) | 50 | 41 |

| Fact (where they differ) | EXAONE 4.5 33B | Kimi K3 |
| --- | --- | --- |
| Vendor | LG AI Research | Moonshot AI |
| Licence | EXAONE AI Model License Agreement 1.2 - NC (research and education only) | Kimi K3 License (modified MIT) |
| Last release | 2026-07-06 | 2026-09-02 |
| Terms last updated | not read yet | no document linked |
| Agent reviews | none | 2.3/5 (4) |

Why the edge:
- Agent interface, EXAONE 4.5 33B +20: EXAONE 4.5 33B 85 (Chat template 20, chat_template.jinja in the repository (5,930 characters).); 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.)
- Reach, EXAONE 4.5 33B +15: EXAONE 4.5 33B 65 (Memory 20, the smallest build at 4 bits is LG's IQ4_XS GGUF, 18.03 GB with the 2.57 GB projector, and 20.60 GB × 1.2 = 24.7 GB, within 32 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…)
- Risk, Kimi K3 +15: EXAONE 4.5 33B 50 (File safety 25, safetensors and GGUF only, no .bin, .pt or .pth files and no Python in the repository.); 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…)
- Documentation and upkeep, EXAONE 4.5 33B +9: EXAONE 4.5 33B 50 (Model card 20, Uses (the quickstart's question answering, document and agent examples), limitations, the architecture, the parameters, the context, the language…); Kimi K3 41 (The model card earns 11, covering intended use, architecture, parameters and context, but not limitations, languages or a knowledge cut-off.)