LFM2.5

LFM2.5

Liquid AI
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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.

About

Nomic Embed is a suite of open source, high-performance embedding models designed for various applications, including multilingual text, multimodal content, and code. The ecosystem includes models like Nomic Embed Text v2, which utilizes a Mixture-of-Experts (MoE) architecture to support over 100 languages with efficient inference using 305M active parameters. Nomic Embed Text v1.5 offers variable embedding dimensions (64 to 768) through Matryoshka Representation Learning, enabling developers to balance performance and storage needs. For multimodal applications, Nomic Embed Vision v1.5 aligns with the text models to provide a unified latent space for text and image data, facilitating seamless multimodal search. Additionally, Nomic Embed Code delivers state-of-the-art performance on code embedding tasks across multiple programming languages.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

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

Audience

Machine learning engineers and developers seeking a solution offering embedding models for multilingual text, multimodal content, and code applications

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Liquid AI
Founded: 2023
United States
www.liquid.ai/blog/introducing-lfm2-5-the-next-generation-of-on-device-ai

Company Information

Nomic
United States
www.nomic.ai/embed

Alternatives

Alternatives

MedGemma

MedGemma

Google DeepMind
HunyuanOCR

HunyuanOCR

Tencent
Qwen2

Qwen2

Alibaba

Categories

Categories

Integrations

Amazon Bedrock
Baseten
ElevenLabs
Gemma 3
Gemma 4
Go
Hugging Face
Java
JavaScript
LEAP
Llama
Llama 3.2
PHP
Python
Qwen3
Ruby

Integrations

Amazon Bedrock
Baseten
ElevenLabs
Gemma 3
Gemma 4
Go
Hugging Face
Java
JavaScript
LEAP
Llama
Llama 3.2
PHP
Python
Qwen3
Ruby
Claim LFM2.5 and update features and information
Claim LFM2.5 and update features and information
Claim Nomic Embed and update features and information
Claim Nomic Embed and update features and information