# GLM-4.7-Flash vs LFM3-VL-2B (slim)

> GLM-4.7-Flash scores 63 (B) to LFM3-VL-2B's 61 (C) for open-weight models you run yourself. 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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GLM-4.7-Flash scores 63 (B) on agent readiness against LFM3-VL-2B's 61 (C), and leads in 1 of 4 scored categories. LFM3-VL-2B leads on reach, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- GLM-4.7-Flash: B 63, rank #26 of 160 open-weight models · https://www.anchorterminal.com/tools/glm-4-7-flash.min.md
- LFM3-VL-2B: C 61, rank #72 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-vl-2b.min.md
- GLM-4.7-Flash, good for Agents and developers who want a small, permissively licensed tool-calling model on one 24 to 32 GB GPU or Mac, in almost any runtime Ahead on Risk, 55 against 40.
- LFM3-VL-2B, good for Agents on a laptop, phone or robot that need to read screens, documents, images and video from a model under 2 GB at 4 bits Ahead on Reach, 85 against 80; Agent interface, 90 against 85; Documentation and upkeep, 77 against 28.

| Category | GLM-4.7-Flash | LFM3-VL-2B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 85 |
| Risk (20%) | 55 | 40 |
| Agent interface (10%) | 85 | 90 |
| Documentation and upkeep (10%) | 28 | 77 |

| Fact (where they differ) | GLM-4.7-Flash | LFM3-VL-2B |
| --- | --- | --- |
| Vendor | Z.ai (Zhipu AI) | Liquid AI |
| Licence | MIT | LFM Open License v1.0 (free commercial use below $10M annual revenue) |
| llms.txt | no | yes |
| Last release | 2026-01-29 | 2026-11-09 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Documentation and upkeep, LFM3-VL-2B +49: GLM-4.7-Flash 28 (The card covers architecture, parameters and languages and misses four of the seven items, for 8. Training data is 0, as the card describes none.); LFM3-VL-2B 77 (Model card 17, Intended use (questions about video, documents, charts and app screens, finding objects, spatial reasoning), a limitation (not recommended for co…)
- Risk, GLM-4.7-Flash +15: GLM-4.7-Flash 55 (File safety is full, with safetensors only and the card loading it through Transformers' own code without remote code.); LFM3-VL-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Reach, LFM3-VL-2B +5: GLM-4.7-Flash 80 (Memory earns 25, since Ollama's smallest build is the 19 GB q4_K_M one, about 22.8 GB with the fifth added, which fits 24 GB.); LFM3-VL-2B 85 (Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB with its 0.20 GB projector file, and 1.30 GB × 1.2 = 1.6 GB, which fits 8 GB, well inside the 16 GB line.)
- Agent interface, LFM3-VL-2B +5: GLM-4.7-Flash 85 (A Jinja chat template sits in the repository, for 20. The tool-calling format is the full 25, because Z.ai itself names the glm47 parser for vLLM and SGLang, sa…); LFM3-VL-2B 90 (Chat template 20, chat_template.jinja in the repository (12,129 characters), with roles, images and video, tools, deferred tools, tool results and the thinking…)