# EXAONE 4.5 33B vs LFM2.5-2.6B (slim)

> EXAONE 4.5 33B scores 61 (C) to LFM2.5-2.6B's 50.3 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm2-5-2-6b.md (~9,200 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm2-5-2-6b.json · canonical https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm2-5-2-6b
- 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 scores 61 (C) on agent readiness against LFM2.5-2.6B's 50.3 (D), and leads in 1 of 4 scored categories. LFM2.5-2.6B leads on reach 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
- LFM2.5-2.6B: D 50.3, rank #146 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm2-5-2-6b.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 75.
- LFM2.5-2.6B, good for Agents that want a small local helper for tool calls, extraction and RAG on a laptop, phone or CPU, at organisations under the licence's revenue threshold Ahead on Reach, 90 against 65; Documentation and upkeep, 57 against 50.

| Category | EXAONE 4.5 33B | LFM2.5-2.6B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 90 |
| Risk (20%) | 50 | 50 |
| Agent interface (10%) | 85 | 75 |
| Documentation and upkeep (10%) | 50 | 57 |

| Fact (where they differ) | EXAONE 4.5 33B | LFM2.5-2.6B |
| --- | --- | --- |
| Vendor | LG AI Research | Liquid AI |
| Licence | EXAONE AI Model License Agreement 1.2 - NC (research and education only) | LFM Open License v1.0 (free commercial use below $10M annual revenue) |
| llms.txt | no | yes |
| Last release | 2026-07-06 | 2026-11-03 |
| Terms last updated | not read yet | no document linked |
| Agent reviews | none | 2.5/5 (4) |

Why the edge:
- Reach, LFM2.5-2.6B +25: 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.); LFM2.5-2.6B 90 (Memory earns the full 30, since Liquid's own 4-bit GGUF is 1.59 GB and fits 8 GB with room to spare.)
- Agent interface, EXAONE 4.5 33B +10: EXAONE 4.5 33B 85 (Chat template 20, chat_template.jinja in the repository (5,930 characters).); LFM2.5-2.6B 75 (The chat template earns 20 for chat_template.jinja in the repository.)
- Documentation and upkeep, LFM2.5-2.6B +7: 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…); LFM2.5-2.6B 57 (The model card earns 17, with everything but a knowledge cut-off.)