# EXAONE 4.5 33B vs LFM3-1.7B (slim)

> EXAONE 4.5 33B and LFM3-1.7B 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.

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- 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 LFM3-1.7B score within a point of each other on agent readiness, 61 (C) and 61 (C). LFM3-1.7B 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
- LFM3-1.7B: C 61, rank #69 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-1-7b.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 Risk, 50 against 40.
- LFM3-1.7B, good for Agents on a laptop, phone or small server that need tool calling and a long context from a model under 2 GB at 4 bits Ahead on Reach, 85 against 65; Agent interface, 100 against 85; Documentation and upkeep, 67 against 50.

| Category | EXAONE 4.5 33B | LFM3-1.7B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 85 |
| Risk (20%) | 50 | 40 |
| Agent interface (10%) | 85 | 100 |
| Documentation and upkeep (10%) | 50 | 67 |

| Fact (where they differ) | EXAONE 4.5 33B | LFM3-1.7B |
| --- | --- | --- |
| 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 | 2026-11-09 |
| Terms last updated | not read yet | no document linked |

Why the edge:
- Reach, LFM3-1.7B +20: 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.); LFM3-1.7B 85 (Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB, and 1.10 GB × 1.2 = 1.3 GB, which fits 8 GB, well inside the 16 GB line.)
- Documentation and upkeep, LFM3-1.7B +17: 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…); LFM3-1.7B 67 (Model card 17, Intended use (local agents, tool calling, structured outputs, fine-tuning), a limitation (not recommended for agentic coding or complex multi-ste…)
- Agent interface, LFM3-1.7B +15: EXAONE 4.5 33B 85 (Chat template 20, chat_template.jinja in the repository (5,930 characters).); LFM3-1.7B 100 (Chat template 20, chat_template.jinja in the repository (12,129 characters), with roles, tools, deferred tools, tool results and the thinking switch.)
- Risk, EXAONE 4.5 33B +10: EXAONE 4.5 33B 50 (File safety 25, safetensors and GGUF only, no .bin, .pt or .pth files and no Python in the repository.); LFM3-1.7B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)