LFM3

LFM3

Liquid AI
Timestral

Timestral

Mistral AI
+
+

Related Products

  • LTX
    182 Ratings
    Visit Website
  • LM-Kit.NET
    29 Ratings
    Visit Website
  • Nexo
    18,780 Ratings
    Visit Website
  • AuctionMethod
    43 Ratings
    Visit Website
  • Google AI Studio
    41 Ratings
    Visit Website
  • Compute with Hivenet
    4 Ratings
    Visit Website
  • Google Cloud Speech-to-Text
    443 Ratings
    Visit Website
  • Mentornity
    99 Ratings
    Visit Website
  • Anaconda
    625 Ratings
    Visit Website
  • IUX
    968 Ratings
    Visit Website

About

LFM3 is Liquid AI’s family of compact, open-weight foundation models for text, vision, audio, and multimodal tasks. The release includes text-generation, vision-language, audio, omni, and decision-model variants. Developers can download the model weights, adapt supported models through fine-tuning, and run them locally on edge hardware or access them through Liquid AI’s hosted API. Use cases include conversational assistants, tool calling, speech transcription and generation, image and video understanding, document extraction, classification, routing, and robotics applications. LFM3 is intended for developers, researchers, and organizations building specialized AI applications that need flexible deployment choices, including local inference. Open-weight models are available under Liquid AI’s LFM Open License; commercial eligibility and terms depend on an organization’s annual revenue.

About

Timestral is a family of time-series foundation models and a Python inference package for generating multivariate probabilistic forecasts from historical sequences. The four model sizes (5M, 28M, 123M and 209M parameters) support past-only, known-future and categorical covariates, return quantile forecasts, and accept context windows up to 32,768 time steps. Developers can load pretrained weights from the Hugging Face Hub or from local files and run inference on CPU or GPU, then incorporate forecasts into monitoring, capacity-planning, energy, supply-chain, financial-risk, or maintenance workflows. Timestral supports zero-shot forecasting and can be adapted to domain data through Mistral Forge. The package is intended for data scientists, machine-learning engineers, and teams building forecasting systems; repository code is Apache 2.0, while model weights use a separate Modified MIT license.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Not Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers, AI researchers, and organizations building specialized AI applications, including applications using local or edge inference.

Audience

Data scientists, machine-learning engineers, forecasting practitioners, and teams developing time-series forecasting systems.

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

No images available

Pricing

$0.08/MTok
LFM3-1.7B API usage is $0.08 per million input tokens, $0.02 per million cached input tokens, and $0.20 per million output tokens. New organizations receive $2 in API credit. Open-weight models can be used in production free by developers, researchers, nonprofits, and businesses with less than $10 million in annual revenue; businesses above that threshold require a paid license.
Free Version Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Supported
Free Trial Not Supported

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 Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Liquid AI
Founded: 2023
United States
www.liquid.ai/blog/lfm3

Company Information

Mistral AI
Founded: 2023
France
github.com/mistralai/timestral

Alternatives

Gemma 4

Gemma 4

Google

Alternatives

TimesFM-3

TimesFM-3

Google
LFM2.5

LFM2.5

Liquid AI
Qwen3.5

Qwen3.5

Alibaba
Inkling

Inkling

Thinking Machines Lab
Solar Mini

Solar Mini

Upstage AI
Qwen3.8-27B

Qwen3.8-27B

Alibaba
Mistral NeMo

Mistral NeMo

Mistral AI

Categories

AI Coding Models Supported
AI Models Supported
Multimodal Models Supported

Categories

AI Models Supported

Integrations

Hugging Face Supported
Hugging Face Transformers Supported
LM Studio Supported
Mistral Forge Not Supported
Ollama Supported
OpenRouter Supported
Unsloth Supported
Vercel AI Gateway Supported
vLLM Supported

Integrations

Hugging Face Not Supported
Hugging Face Transformers Not Supported
LM Studio Not Supported
Mistral Forge Supported
Ollama Not Supported
OpenRouter Not Supported
Unsloth Not Supported
Vercel AI Gateway Not Supported
vLLM Not Supported
Claim LFM3 and update features and information
Claim LFM3 and update features and information
Claim Timestral and update features and information
Claim Timestral and update features and information