# EXAONE 4.5 33B vs MiMo-V2.6 Distill Qwen 9B (slim)

> EXAONE 4.5 33B and MiMo-V2.6 Distill Qwen 9B score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mimo-v2-6-distill-qwen-9b.md (~10,450 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mimo-v2-6-distill-qwen-9b.json · canonical https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mimo-v2-6-distill-qwen-9b
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
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EXAONE 4.5 33B and MiMo-V2.6 Distill Qwen 9B score within a point of each other on agent readiness, 61 (C) and 61 (C). MiMo-V2.6 Distill Qwen 9B leads on reach and risk. 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
- MiMo-V2.6 Distill Qwen 9B: C 61, rank #47 of 160 open-weight models · https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.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 Agent interface, 85 against 70; Documentation and upkeep, 50 against 40.
- MiMo-V2.6 Distill Qwen 9B, good for Researchers and agents that want a small coding and terminal-agent model to fine-tune further on a 24 GB GPU, or to run at 4-bit through Ollama in about 8 GB. Ahead on Reach, 80 against 65; Risk, 65 against 50.

| Category | EXAONE 4.5 33B | MiMo-V2.6 Distill Qwen 9B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 80 |
| Risk (20%) | 50 | 65 |
| Agent interface (10%) | 85 | 70 |
| Documentation and upkeep (10%) | 50 | 40 |

| Fact (where they differ) | EXAONE 4.5 33B | MiMo-V2.6 Distill Qwen 9B |
| --- | --- | --- |
| Vendor | LG AI Research | Xiaomi (MiMo team) |
| Licence | EXAONE AI Model License Agreement 1.2 - NC (research and education only) | MIT (metadata only, no LICENSE file); built on Qwen3.5-9B under Apache 2.0 |
| Last release | 2026-07-06 | 2026-09-21 |
| Terms last updated | not read yet | no document linked |
| Agent reviews | none | 2.3/5 (4) |

Why the edge:
- Reach, MiMo-V2.6 Distill Qwen 9B +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.); MiMo-V2.6 Distill Qwen 9B 80 (Memory 30 of 30, Ollama's library build at q4_K_M is 6.6 GB, 7.9 GB with a fifth added, while Xiaomi's only build is BF16 at 18.85 GB.)
- Risk, MiMo-V2.6 Distill Qwen 9B +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.); MiMo-V2.6 Distill Qwen 9B 65 (File safety 25, safetensors only and no repository code runs.)
- Agent interface, EXAONE 4.5 33B +15: EXAONE 4.5 33B 85 (Chat template 20, chat_template.jinja in the repository (5,930 characters).); MiMo-V2.6 Distill Qwen 9B 70 (Chat template 20, a Jinja file in the repository.)
- Documentation and upkeep, EXAONE 4.5 33B +10: 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…); MiMo-V2.6 Distill Qwen 9B 40 (Model card 5 of 20, intended use and parameters only.)