# Apertus v1.5 8B vs LFM3-Omni-2B (slim)

> Apertus v1.5 8B and LFM3-Omni-2B 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.

- Full: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lfm3-omni-2b.md (~9,600 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lfm3-omni-2b.json · canonical https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lfm3-omni-2b
- 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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Apertus v1.5 8B and LFM3-Omni-2B score within a point of each other on agent readiness, 61 (C) and 61 (C). LFM3-Omni-2B leads on reach. Both do open-weight models you run yourself.

- Apertus v1.5 8B: C 61, rank #40 of 160 open-weight models · https://www.anchorterminal.com/tools/apertus-v1-5-8b.min.md
- LFM3-Omni-2B: C 61, rank #71 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-omni-2b.min.md
- Apertus v1.5 8B, good for Agents that want a fully open, multilingual 8B with image and audio input on one 24 GB GPU, and can run a publisher fork of vLLM. Ahead on Risk, 75 against 40; Agent interface, 85 against 70; Documentation and upkeep, 84 against 49.
- LFM3-Omni-2B, good for Voice and camera agents on a laptop or phone that want one small model for hearing, seeing, speaking and calling tools Ahead on Reach, 80 against 40.

| Category | Apertus v1.5 8B | LFM3-Omni-2B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 40 | 80 |
| Risk (20%) | 75 | 40 |
| Agent interface (10%) | 85 | 70 |
| Documentation and upkeep (10%) | 84 | 49 |

| Fact (where they differ) | Apertus v1.5 8B | LFM3-Omni-2B |
| --- | --- | --- |
| Vendor | Swiss AI Initiative (EPFL and ETH Zurich) | Liquid AI |
| Licence | Apache-2.0, with the Apertus Acceptable Use Policy (v1.5, 14 July 2026) accepted at the download gate | LFM Open License v1.0 (free commercial use below $10M annual revenue) |
| llms.txt | no | yes |
| Last release | 2026-10-14 | 2026-11-03 |
| Terms last updated | not read yet | no document linked |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Reach, LFM3-Omni-2B +40: Apertus v1.5 8B 40 (Memory 25 of 30, the BF16 files are 18.4 GB, or 22.1 GB with a fifth added, which fits 24 GB.); LFM3-Omni-2B 80 (Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB with its 0.29 GB projector file, and 1.39 GB × 1.2 = 1.7 GB, which fits 8 GB, well inside the 16 GB line.)
- Risk, Apertus v1.5 8B +35: Apertus v1.5 8B 75 (File safety 25, safetensors only and no code in the repository.); LFM3-Omni-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Documentation and upkeep, Apertus v1.5 8B +35: Apertus v1.5 8B 84 (Model card 14 of 20, languages and a knowledge cut-off are missing.); LFM3-Omni-2B 49 (Model card 14, Intended use (one on-device model in place of separate speech recognition, vision, language and speech models), architecture, parameters (2.17B)…)
- Agent interface, Apertus v1.5 8B +15: Apertus v1.5 8B 85 (Chat template 20, a Jinja file in the repository.); LFM3-Omni-2B 70 (Chat template 20, chat_template.jinja in the repository (13,513 characters), with roles, images, video and audio, tools, deferred tools and tool results.)