# LFM3-VL-2B vs Qwen3.5-397B-A17B (slim)

> Qwen3.5-397B-A17B scores 64.1 (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.

- Full: https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-qwen3-5-397b-a17b.md (~9,800 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-qwen3-5-397b-a17b.json · canonical https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-qwen3-5-397b-a17b
- 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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Qwen3.5-397B-A17B scores 64.1 (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.

- LFM3-VL-2B: C 61, rank #72 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-vl-2b.min.md
- Qwen3.5-397B-A17B: B 64.1, rank #23 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-397b-a17b.min.md
- 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 70; Agent interface, 90 against 70; Documentation and upkeep, 77 against 34.
- Qwen3.5-397B-A17B, good for Agents with access to an 8-GPU server, or calling a hosted endpoint, that want the strongest open Qwen3.5 with vision and a plain licence. Ahead on Risk, 55 against 40.

| Category | LFM3-VL-2B | Qwen3.5-397B-A17B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 70 |
| Risk (20%) | 40 | 55 |
| Agent interface (10%) | 90 | 70 |
| Documentation and upkeep (10%) | 77 | 34 |

| Fact (where they differ) | LFM3-VL-2B | Qwen3.5-397B-A17B |
| --- | --- | --- |
| Vendor | Liquid AI | Alibaba (Qwen team) |
| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | Apache-2.0 |
| llms.txt | yes | no |
| Last release | 2026-11-09 | 2026-02-16 |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Documentation and upkeep, LFM3-VL-2B +43: 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…); Qwen3.5-397B-A17B 34 (The card covers five of the seven items and misses limitations and a cut-off (14).)
- Agent interface, LFM3-VL-2B +20: 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…); Qwen3.5-397B-A17B 70 (The template ships in the repository (20) and renders several tool calls per turn for a model trained for tool use (20).)
- Reach, LFM3-VL-2B +15: 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.); Qwen3.5-397B-A17B 70 (Memory scores 0, since even the smallest 4-bit build, LM Studio's MLX 4-bit at 223.9 GB, needs about 269 GB with a fifth added, and Alibaba's own GPTQ-Int4 abou…)
- Risk, Qwen3.5-397B-A17B +15: LFM3-VL-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Qwen3.5-397B-A17B 55 (Safetensors only with no repository code run on load or to build prompts gives file safety 25, and files in the Qwen organisation the publisher's GitHub links t…)