# LFM3-VL-2B vs Ripple-65B Preview (slim)

> LFM3-VL-2B scores 61 (C) to Ripple-65B Preview's 53.3 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-ripple-65b-preview.md (~9,650 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-ripple-65b-preview.json · canonical https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-ripple-65b-preview
- 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
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

LFM3-VL-2B scores 61 (C) on agent readiness against Ripple-65B Preview's 53.3 (D), and leads in 3 of 4 scored categories. Ripple-65B Preview leads on risk. 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
- Ripple-65B Preview: D 53.3, rank #135 of 160 open-weight models · https://www.anchorterminal.com/tools/ripple-65b-preview.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 45; Agent interface, 90 against 75; Documentation and upkeep, 77 against 49.
- Ripple-65B Preview, good for Teams with Blackwell GPUs or a DGX Spark who want an Apache 2.0 coding model to try for terminal and agentic coding work, and can run the publisher's code to serve it. Ahead on Risk, 55 against 40.

| Category | LFM3-VL-2B | Ripple-65B Preview |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 45 |
| Risk (20%) | 40 | 55 |
| Agent interface (10%) | 90 | 75 |
| Documentation and upkeep (10%) | 77 | 49 |

| Fact (where they differ) | LFM3-VL-2B | Ripple-65B Preview |
| --- | --- | --- |
| Vendor | Liquid AI | Ricursive Intelligence |
| 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 | 2026-11-04 |
| Terms last updated | no document linked | not read yet |

Why the edge:
- Reach, LFM3-VL-2B +40: 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.); Ripple-65B Preview 45 (Memory 10 of 30, the smallest 4-bit build is Ricursive's NVFP4 at 57.2 GB, 68.7 GB with a fifth added, which is over 64 GB and fits our reference machine.)
- Documentation and upkeep, LFM3-VL-2B +28: 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…); Ripple-65B Preview 49 (Model card 14 of 20, no limitations and no knowledge cut-off.)
- Risk, Ripple-65B Preview +15: LFM3-VL-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Ripple-65B Preview 55 (File safety 15, safetensors only, less 10 because the documented way to run it loads Ricursive's Python.)
- Agent interface, LFM3-VL-2B +15: 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…); Ripple-65B Preview 75 (Chat template 20, chat_template.jinja in the repository.)