# EXAONE 4.5 33B vs Mistral Large 4 (slim)

> EXAONE 4.5 33B scores 61 (C) to Mistral Large 4's 54.6 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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EXAONE 4.5 33B scores 61 (C) on agent readiness against Mistral Large 4's 54.6 (C), and leads in 1 of 4 scored categories. Mistral Large 4 leads on risk, 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
- Mistral Large 4: C 54.6, rank #128 of 160 open-weight models · https://www.anchorterminal.com/tools/mistral-large-4.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.
- Mistral Large 4, good for Operators with an 8-GPU Blackwell or H200 node who want a frontier-sized open model for coding agents and defensive security, with a hosted twin on Mistral's API. Ahead on Risk, 75 against 50; Agent interface, 95 against 85; Documentation and upkeep, 64 against 50.

| Category | EXAONE 4.5 33B | Mistral Large 4 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 50 |
| Risk (20%) | 50 | 75 |
| Agent interface (10%) | 85 | 95 |
| Documentation and upkeep (10%) | 50 | 64 |

| Fact (where they differ) | EXAONE 4.5 33B | Mistral Large 4 |
| --- | --- | --- |
| Vendor | LG AI Research | Mistral AI |
| Licence | EXAONE AI Model License Agreement 1.2 - NC (research and education only) | Mistral Ecosystem Open-Weight License (modified MIT) |
| Last release | 2026-07-06 | 2026-10-29 |
| Terms last updated | not read yet | no document linked |

Why the edge:
- Risk, Mistral Large 4 +25: EXAONE 4.5 33B 50 (File safety 25, safetensors and GGUF only, no .bin, .pt or .pth files and no Python in the repository.); Mistral Large 4 75 (File safety scores 25, safetensors only and loaded by Transformers' own code with a Jinja template.)
- 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.); Mistral Large 4 50 (Memory scores 0, since the smallest 4-bit build, Mistral's NVFP4, is 610 GB, about 732 GB with a fifth added, far above 256 GB.)
- Documentation and upkeep, Mistral Large 4 +14: 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…); Mistral Large 4 64 (The card covers intended use, architecture, parameters, context and languages, and misses limitations and a cut-off (14).)
- Agent interface, Mistral Large 4 +10: EXAONE 4.5 33B 85 (Chat template 20, chat_template.jinja in the repository (5,930 characters).); Mistral Large 4 95 (The chat template is in the repository (20).)