EmbeddingGemma 2Google
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LFM2.5Liquid AI
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Related Products
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About
EmbeddingGemma 2 is an open, lightweight multimodal embedding model designed to map text, code, images, video, and audio into a shared embedding space for search, retrieval, classification, routing, and RAG applications. Built on the Gemma 4 architecture and released under the Apache 2.0 license, it has 740 million parameters and is optimized for on-device inference. Its modular design can use as little as 270M parameters for text-only workloads, with optional vision and audio encoders for full multimodal support. Matryoshka Representation Learning lets developers reduce output vectors from 768 dimensions to 512, 256, or 128, lowering storage and memory requirements for local vector databases. The model supports an 8K-token context window and can process up to 5.5 minutes of audio, 29 images, 58 video frames, or interleaved combinations on local hardware.
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About
Liquid AI’s LFM2.5 is the next generation of on-device AI foundation models designed to deliver high-performance, efficient AI inference on edge devices such as phones, laptops, vehicles, IoT systems, and embedded hardware without relying on cloud compute. It extends the previous LFM2 architecture by significantly increasing the pretraining scale and reinforcement learning stages, yielding a family of hybrid models around 1.2 billion parameters that balance instruction following, reasoning, and multimodal capabilities for real-world agentic use cases. The LFM2.5 family includes Base (for fine-tuning and customization), Instruct (general-purpose instruction-tuned), Japanese-optimized, Vision-Language, and Audio-Language variants, all optimized for fast, on-device inference under tight memory constraints and available as open-weight models deployable via frameworks like llama.cpp, MLX, vLLM, and ONNX.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Supported
iPad
Supported
Android
Supported
Chromebook
Not Supported
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Audience
Developers and AI teams wanting to build private, efficient, on-device multimodal search, retrieval, RAG, and semantic indexing systems
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Audience
Developers and organizations building on-device AI applications and intelligent agents that need efficient, high-quality AI models capable of running locally on consumer, edge, or embedded hardware
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Not Supported
Free Trial
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Pricing
Free
Free Version
Supported
Free Trial
Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
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In Person
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
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Company InformationGoogle
Founded: 1998
United States
blog.google/innovation-and-ai/technology/developers-tools/embeddinggemma-2/
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Company InformationLiquid AI
Founded: 2023
United States
www.liquid.ai/blog/introducing-lfm2-5-the-next-generation-of-on-device-ai
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Alternatives |
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Categories |
Categories |
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Integrations
Amazon Bedrock
Not Supported
ElevenLabs
Not Supported
Gemma 3
Not Supported
Gemma 4
Not Supported
Hugging Face
Not Supported
LEAP
Not Supported
Llama
Not Supported
Llama 3.2
Not Supported
Qwen3
Not Supported
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Integrations
Amazon Bedrock
Supported
ElevenLabs
Supported
Gemma 3
Supported
Gemma 4
Supported
Hugging Face
Supported
LEAP
Supported
Llama
Supported
Llama 3.2
Supported
Qwen3
Supported
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