AI model guide · Liquid AI
LFM3 Omni: What It Is, What It Costs, How to Use It
LFM3 Omni (LFM3-Omni-2B) is Liquid AI’s roughly 2.17B on-device omni model: text, image, video, and audio in; text and speech out; about 32K context; released under the LFM Open License v1.0. It targets spoken visual Q&A, audio-visual video understanding, and multimodal tool calling. Weights are on Hugging Face; compute cost is primarily your hardware (hosted pricing, if any, must be verified with Liquid).
Note: Reviewed against Liquid’s blog, model card, and documentation on (Asia/Shanghai). License terms and hosted offerings can change—read official pages before shipping.
What LFM3 Omni is
- Vendor: Liquid AI; LFM3 model family.
- Model: LFM3-Omni-2B (~2.17B parameters), on-device-oriented omni model.
- Inputs: Text, image, video, audio.
- Outputs: Text and speech.
- Context: ~32K tokens (confirm on model card).
- What it can do: Spoken VQA, audio-visual video understanding, multimodal tool calling.
- License: LFM Open License v1.0 (open weights—read terms).
- Surfaces: Hugging Face weights + Liquid docs / blog; self-host on your hardware.
Pricing
Open weights mean there is no required subscription to download the model. Your cost is electricity / device silicon or rented GPUs. Hosted inference is a separate service; this guide does not list a confirmed hosted API price.
| Path | Cost | Notes |
|---|---|---|
| Open weights (self-host) | Your hardware / cloud GPU | LFM Open License v1.0. License included with the model weights |
| Hosted Liquid endpoint (if offered) | No confirmed rate listed in this guide | Hosted service availability and charges are separate from downloading the model. |
| Edge / on-device deployment | Device hardware and electricity | Performance depends on chip + quantization. Measure latency and memory on the intended device |
How to get started
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Read the LFM3 announcement
Start with Liquid’s LFM3 blog for family positioning and omni capabilities.
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Download weights
Pull LiquidAI/LFM3-Omni-2B from Hugging Face and review the LFM Open License v1.0 text bundled with the card.
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Follow official docs
Use docs.liquid.ai — LFM3-Omni-2B for loaders, modality I/O, and tool-calling notes.
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Run a multimodal smoke test
Try one spoken VQA prompt and one short video+audio clip on hardware you control. Measure latency and memory before committing to an device deployment.
How LFM3 Omni compares
Compare LFM3 Omni with the specific Qwen multimodal model or other alternative you can run on your hardware. Family names alone do not determine memory requirements or supported inputs.
| Area | Question | Suggested test |
|---|---|---|
| Modalities | Does the model handle your actual inputs and outputs? | Test an image question, a short video, and a spoken exchange. |
| Device performance | Is latency and memory use acceptable? | Measure the same workload and quantization on the intended device. |
| Deployment terms | Can you distribute and operate the model as planned? | Review each model license and the cost of your own hosting. |
Official sources
FAQ
What is LFM3 Omni?
LFM3 Omni (LFM3-Omni-2B) is Liquid AI’s ~2.17B on-device omni model. It accepts text, image, video, and audio inputs and produces text and speech outputs, with about 32K context, under the LFM Open License v1.0.
Who makes LFM3 Omni?
Liquid AI builds the LFM3 family, including LFM3-Omni-2B. Model cards and docs are published on liquid.ai, Hugging Face (LiquidAI/LFM3-Omni-2B), and docs.liquid.ai. Always read the LFM Open License v1.0 before redistribution or commercial use.
How much does LFM3 Omni cost?
Weights are open under LFM Open License v1.0—your cost is mainly your own hardware (or cloud GPUs you rent). Any hosted Liquid endpoint pricing should be verified on Liquid’s site; do not assume a free hosted API.
What modalities does LFM3-Omni-2B support?
Inputs: text, image, video, and audio. Outputs: text and speech. Vendor materials highlight spoken visual Q&A, audio-visual video understanding, and multimodal tool calling.
What is the context window?
Public materials describe about a 32K-token context window for LFM3-Omni-2B. Confirm exact limits on the Hugging Face model card and Liquid docs before sizing long multimodal sessions.
Is LFM3 Omni open source / open weights?
Liquid publishes open weights under LFM Open License v1.0. Read that license for redistribution and commercial terms before shipping a product on top of the weights.
Can it run on-device?
Yes—the ~2.17B multimodal model is positioned for on-device / edge deployment. Actual FPS and battery impact depend on your chip, quantization, and whether you enable speech output.
How does it compare to Qwen Omni-class models?
Both target small multimodal “omni” assistants (text/vision/audio). LFM3 Omni emphasizes Liquid’s on-device stack and open license; Qwen Omni-class models have their own sizes and licenses. Compare qualitatively on your hardware. Test both with the same inputs and compare memory use, latency, and output quality.
Where do I download LFM3-Omni-2B?
Use the Hugging Face repository LiquidAI/LFM3-Omni-2B for weights and card details, and Liquid’s LFM3 blog plus docs.liquid.ai for loaders, demos, modality notes, and the LFM Open License v1.0 text.
How do I get started?
Read the LFM3 blog, pull the HF weights, run a spoken VQA or short video+audio prompt on a machine you control, then decide whether edge hardware or a self-hosted GPU is enough before looking at any hosted Liquid options.
Is this page affiliated with Liquid AI?
No. This is an independent FAQ-style explainer on AI Model FAQ. Confirm licenses, hardware requirements, and any hosted pricing on official Liquid / Hugging Face pages before deploying or shipping a product.
Updated (Asia/Shanghai). Not affiliated with Liquid AI, Hugging Face, or Alibaba / Qwen.