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Average Ratings 0 Ratings
Description
Devstral is a collaborative effort between Mistral AI and All Hands AI, resulting in an open-source large language model specifically tailored for software engineering. This model demonstrates remarkable proficiency in navigating intricate codebases, managing edits across numerous files, and addressing practical problems, achieving a notable score of 46.8% on the SWE-Bench Verified benchmark, which is superior to all other open-source models. Based on Mistral-Small-3.1, Devstral boasts an extensive context window supporting up to 128,000 tokens. It is designed for optimal performance on high-performance hardware setups, such as Macs equipped with 32GB of RAM or Nvidia RTX 4090 GPUs, and supports various inference frameworks including vLLM, Transformers, and Ollama. Released under the Apache 2.0 license, Devstral is freely accessible on platforms like Hugging Face, Ollama, Kaggle, Unsloth, and LM Studio, allowing developers to integrate its capabilities into their projects seamlessly. This model not only enhances productivity for software engineers but also serves as a valuable resource for anyone working with code.
Description
LFM3 represents Liquid AI's suite of streamlined, open-weight foundational models designed for a variety of applications, including text, vision, audio, and multimodal tasks. This lineup features variants for text generation, vision-language processing, audio, omni tasks, and decision-making models. Developers have the option to download the model weights, customize the supported models via fine-tuning, and deploy them on local edge hardware, or alternatively, utilize Liquid AI’s hosted API for access. Potential applications encompass conversational agents, tool invocation, speech transcription and synthesis, understanding of images and videos, document extraction, classification, routing, and robotics functionalities. LFM3 aims to cater to developers, researchers, and organizations focused on creating tailored AI solutions that require adaptable deployment options, including the ability for local inference. Furthermore, the open-weight models operate under Liquid AI’s LFM Open License, where the eligibility for commercial use and its associated terms are contingent upon the annual revenue of the organization. This flexibility allows users to tailor their AI implementations precisely to their needs, enhancing the overall utility of the models.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Hugging Face
Yes
LM Studio
Yes
Ollama
Yes
Unsloth
Yes
Hugging Face Transformers
No
Kaggle
Yes
Mistral AI
Yes
Mistral Code
Yes
OpenRouter
No
Vercel AI Gateway
No
Integrations
Hugging Face
Yes
LM Studio
Yes
Ollama
Yes
Unsloth
Yes
Hugging Face Transformers
Yes
Kaggle
No
Mistral AI
No
Mistral Code
No
OpenRouter
Yes
Vercel AI Gateway
Yes
Pricing Details
$0.1 per million input tokens
Free Trial
No
Free Version
Yes
Pricing Details
$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 Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
Yes
iPad App
Yes
Android App
Yes
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
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)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Mistral AI
Founded
2023
Country
France
Website
mistral.ai/news/devstral
Vendor Details
Company Name
Liquid AI
Founded
2023
Country
United States
Website
www.liquid.ai/blog/lfm3