# LFM3-VL-2B vs Nanbeige4.3-33B (slim)

> LFM3-VL-2B and Nanbeige4.3-33B score within a point of each other for open-weight models you run yourself, 61 and 60.8 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-nanbeige-4-3-33b.md (~9,700 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-nanbeige-4-3-33b.json · canonical https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-nanbeige-4-3-33b
- 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 and Nanbeige4.3-33B score within a point of each other on agent readiness, 61 (C) and 60.8 (C). Nanbeige4.3-33B 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
- Nanbeige4.3-33B: C 60.8, rank #86 of 160 open-weight models · https://www.anchorterminal.com/tools/nanbeige-4-3-33b.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 80; Agent interface, 90 against 85; Documentation and upkeep, 77 against 56.
- Nanbeige4.3-33B, good for Agents with a 32 GB GPU (INT4) or more, or the 128 GB reference machine at BF16, that want an Apache-tagged 33B model for long coding and tool loops. Ahead on Risk, 60 against 40.

| Category | LFM3-VL-2B | Nanbeige4.3-33B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 80 |
| Risk (20%) | 40 | 60 |
| Agent interface (10%) | 90 | 85 |
| Documentation and upkeep (10%) | 77 | 56 |

| Fact (where they differ) | LFM3-VL-2B | Nanbeige4.3-33B |
| --- | --- | --- |
| Vendor | Liquid AI | Nanbeige LLM Lab (BOSS Zhipin) |
| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) |
| llms.txt | yes | no |
| Last release | 2026-11-09 | 2026-10-31 |

Why the edge:
- Documentation and upkeep, LFM3-VL-2B +21: 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…); Nanbeige4.3-33B 56 (The model card earns 11, with intended use, parameters, context and languages but no limitations, architecture or cut-off.)
- Risk, Nanbeige4.3-33B +20: LFM3-VL-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Nanbeige4.3-33B 60 (File safety earns 25, safetensors only and no repository code, so the card's trust_remote_code has nothing to run.)
- Reach, LFM3-VL-2B +5: 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.); Nanbeige4.3-33B 80 (Memory earns 20, since Nanbeige's INT4 build is 22.57 GB, about 27 GB with a fifth added, which fits 32 GB.)
- Agent interface, LFM3-VL-2B +5: 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…); Nanbeige4.3-33B 85 (The chat template earns 20, Jinja in tokenizer_config.json.)