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What is Stable LM?

Stable LM signifies a notable progression in the language model domain, building upon prior open-source experiences, especially through collaboration with EleutherAI, a nonprofit research group. This evolution has included the creation of prominent models like GPT-J, GPT-NeoX, and the Pythia suite, all trained on The Pile open-source dataset, with several recent models such as Cerebras-GPT and Dolly-2 taking cues from this foundational work. In contrast to earlier models, Stable LM utilizes a groundbreaking dataset that is three times as extensive as The Pile, comprising an impressive 1.5 trillion tokens. More details regarding this dataset will be disclosed soon. The vast scale of this dataset allows Stable LM to perform exceptionally well in conversational and programming tasks, even though it has a relatively compact parameter size of 3 to 7 billion compared to larger models like GPT-3, which features 175 billion parameters. Built for adaptability, Stable LM 3B is a streamlined model designed to operate efficiently on portable devices, including laptops and mobile gadgets, which excites us about its potential for practical usage and portability. This innovation has the potential to bridge the gap for users seeking advanced language capabilities in accessible formats, thus broadening the reach and impact of language technologies. Overall, the launch of Stable LM represents a crucial advancement toward developing more efficient and widely available language models for diverse users.

What is Devstral Small 2?

Devstral Small 2 is a condensed, 24 billion-parameter variant of Mistral AI's groundbreaking coding-focused models, made available under the adaptable Apache 2.0 license to support both local use and API access. Alongside its more extensive sibling, Devstral 2, it offers "agentic coding" capabilities tailored for low-computational environments, featuring a substantial 256K-token context window that enables it to understand and alter entire codebases with ease. With a performance score nearing 68.0% on the widely recognized SWE-Bench Verified code-generation benchmark, Devstral Small 2 distinguishes itself within the realm of open-weight models that are much larger. Its compact structure and efficient design allow it to function effectively on a single GPU or even in CPU-only setups, making it an excellent option for developers, small teams, or hobbyists who may lack access to extensive data-center facilities. Moreover, despite being smaller, Devstral Small 2 retains critical functionalities found in its larger counterparts, such as the capability to reason through multiple files and adeptly manage dependencies, ensuring that users enjoy substantial coding support. This combination of efficiency and high performance positions it as an indispensable asset for the coding community. Additionally, its user-friendly approach ensures that both novice and experienced programmers can leverage its capabilities without significant barriers.

Media

Media

Integrations Supported

Alpaca
Automi
Gopher

Integrations Supported

Cline
Devstral 2
Kilo Code
Mistral AI
Nebius Token Factory

API Availability

API Availability

Has API

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Not specified

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

Stability AI

Date Founded

2019

Company Location

United Kingdom

Company Website

stability.ai/

Company Facts

Organization Name

Mistral AI

Date Founded

2023

Company Location

France

Company Website

mistral.ai/news/devstral-2-vibe-cli

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

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