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features
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support

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Description

LFM2 represents an advanced series of on-device foundation models designed to provide a remarkably swift generative-AI experience across a diverse array of devices. By utilizing a novel hybrid architecture, it achieves decoding and pre-filling speeds that are up to twice as fast as those of similar models, while also enhancing training efficiency by as much as three times compared to its predecessor. These models offer a perfect equilibrium of quality, latency, and memory utilization suitable for embedded system deployment, facilitating real-time, on-device AI functionality in smartphones, laptops, vehicles, wearables, and various other platforms, which results in millisecond inference, device durability, and complete data sovereignty. LFM2 is offered in three configurations featuring 0.35 billion, 0.7 billion, and 1.2 billion parameters, showcasing benchmark results that surpass similarly scaled models in areas including knowledge recall, mathematics, multilingual instruction adherence, and conversational dialogue assessments. With these capabilities, LFM2 not only enhances user experience but also sets a new standard for on-device AI performance.

Description

We are excited to announce the launch of Phi-2, a language model featuring 2.7 billion parameters that excels in reasoning and language comprehension, achieving top-tier results compared to other base models with fewer than 13 billion parameters. In challenging benchmarks, Phi-2 competes with and often surpasses models that are up to 25 times its size, a feat made possible by advancements in model scaling and meticulous curation of training data. Due to its efficient design, Phi-2 serves as an excellent resource for researchers interested in areas such as mechanistic interpretability, enhancing safety measures, or conducting fine-tuning experiments across a broad spectrum of tasks. To promote further exploration and innovation in language modeling, Phi-2 has been integrated into the Azure AI Studio model catalog, encouraging collaboration and development within the research community. Researchers can leverage this model to unlock new insights and push the boundaries of language technology.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Airtrain No 
Axolotl No 
Database Mart No 
Hugging Face Yes 
LLaMA-Factory No 
LM-Kit.NET No 
Microsoft Azure No 
NativeMind No 
OpenAI Yes 
OpenRouter Yes 
Oumi No 
Private LLM No 
Qwen3 Yes 
Runpod No 
Together AI Yes 

Integrations

Airtrain Yes 
Axolotl Yes 
Database Mart Yes 
Hugging Face No 
LLaMA-Factory Yes 
LM-Kit.NET Yes 
Microsoft Azure Yes 
NativeMind Yes 
OpenAI No 
OpenRouter No 
Oumi Yes 
Private LLM Yes 
Qwen3 No 
Runpod Yes 
Together AI No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Liquid AI

Founded

2023

Country

United States

Website

www.liquid.ai/blog/liquid-foundation-models-v2-our-second-series-of-generative-ai-models

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

microsoft.com

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