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What is distil labs?

Distil Labs improves the efficiency of AI by replacing expensive calls to sophisticated models with custom small language models tailored for particular tasks, all while maintaining high-quality benchmarks. They analyze real production traffic and collect traces from current large language model requests to create a comprehensive evaluation set that reveals genuine workload characteristics. Subsequently, the company develops and validates synthetic training data, ensuring that its distribution aligns with the desired workload, and employs supervised fine-tuning in conjunction with reinforcement learning techniques. Once the model is quantized, an optimized endpoint is created to support its deployment. The results are rigorously compared to the existing model in terms of accuracy, latency, and overall efficiency, offering teams the information necessary to decide when to scale up traffic. Furthermore, the OpenAI-compatible endpoint incorporates a specialized small language model, prompt optimization, efficient caching, and enhanced serving tailored for specific applications, thereby guaranteeing optimal performance. By adopting this thorough methodology, organizations are empowered to fully leverage the capabilities of their AI solutions, ultimately driving greater innovation and effectiveness within their operations.

What is Llama 3.1?

We are excited to unveil an open-source AI model that offers the ability to be fine-tuned, distilled, and deployed across a wide range of platforms. Our latest instruction-tuned model is available in three different sizes: 8B, 70B, and 405B, allowing you to select an option that best fits your unique needs. The open ecosystem we provide accelerates your development journey with a variety of customized product offerings tailored to meet your specific project requirements. You can choose between real-time inference and batch inference services, depending on what your project requires, giving you added flexibility to optimize performance. Furthermore, downloading model weights can significantly enhance cost efficiency per token while you fine-tune the model for your application. To further improve performance, you can leverage synthetic data and seamlessly deploy your solutions either on-premises or in the cloud. By taking advantage of Llama system components, you can also expand the model's capabilities through the use of zero-shot tools and retrieval-augmented generation (RAG), promoting more agentic behaviors in your applications. Utilizing the extensive 405B high-quality data enables you to fine-tune specialized models that cater specifically to various use cases, ensuring that your applications function at their best. In conclusion, this empowers developers to craft innovative solutions that not only meet efficiency standards but also drive effectiveness in their respective domains, leading to a significant impact on the technology landscape.

Media

Media

Integrations Supported

AICamp
Alpaca
AnyAPI
ChatLLM
ConsoleX
Cyte
Database Mart
Decopy AI
Featherless
Gemini 2.0 Flash-Lite
Graydient AI
Klee
NinjaTools.ai
Not Diamond
Phala
PromptPal
Runpod
Simplismart
Tune Studio
WebLLM

Integrations Supported

AICamp
Alpaca
AnyAPI
ChatLLM
ConsoleX
Cyte
Database Mart
Decopy AI
Featherless
Gemini 2.0 Flash-Lite
Graydient AI
Klee
NinjaTools.ai
Not Diamond
Phala
PromptPal
Runpod
Simplismart
Tune Studio
WebLLM

API Availability

Has API

API Availability

Has API

Pricing Information

$0.04 per 1M tokens
Free Version
Free Trial Offered?

Pricing Information

Free
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

distil labs

Date Founded

2024

Company Location

Germany

Company Website

www.distillabs.ai/

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

llama.meta.com

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