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features
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support

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Description

You can develop on your laptop, then scale the same Python code elastically across hundreds or GPUs on any cloud. Ray converts existing Python concepts into the distributed setting, so any serial application can be easily parallelized with little code changes. With a strong ecosystem distributed libraries, scale compute-heavy machine learning workloads such as model serving, deep learning, and hyperparameter tuning. Scale existing workloads (e.g. Pytorch on Ray is easy to scale by using integrations. Ray Tune and Ray Serve native Ray libraries make it easier to scale the most complex machine learning workloads like hyperparameter tuning, deep learning models training, reinforcement learning, and training deep learning models. In just 10 lines of code, you can get started with distributed hyperparameter tune. Creating distributed apps is hard. Ray is an expert in distributed execution.

Description

Distil Labs enhances AI performance by substituting costly calls to advanced models with tailored small language models designed for specific tasks while ensuring the quality standards are upheld. By monitoring real production traffic and gathering traces from current LLM requests, it constructs an evaluation set to gain insights into actual workload behavior. Following this, the company creates and verifies synthetic training data, aligns the data distribution with the intended workload, and engages in supervised fine-tuning alongside reinforcement learning. The model is then quantized, and an optimized endpoint is established. The outcomes are systematically assessed against the existing model concerning accuracy, latency, and efficiency, providing teams with data to determine when to increase traffic. Ultimately, the OpenAI-compatible endpoint features a specialized small language model, prompt optimization, effective caching, and refined serving tailored for the specific application, ensuring maximum performance. This comprehensive approach allows organizations to maximize the potential of their AI implementations.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
Anyscale
Apache Airflow
Databricks
Feast
Flyte
GPT-5.4 nano
Gemini 2.0 Flash-Lite
Google Cloud Platform
Google Kubernetes Engine (GKE)
Kubernetes
MLflow
PyTorch
Python
Snowflake
TensorFlow
Union Cloud

Integrations

Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
Anyscale
Apache Airflow
Databricks
Feast
Flyte
GPT-5.4 nano
Gemini 2.0 Flash-Lite
Google Cloud Platform
Google Kubernetes Engine (GKE)
Kubernetes
MLflow
PyTorch
Python
Snowflake
TensorFlow
Union Cloud

Pricing Details

Free
Open source. Consumption-based.
Free Trial
Free Version

Pricing Details

$0.04 per 1M tokens
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Anyscale

Founded

2019

Country

United States

Website

ray.io

Vendor Details

Company Name

distil labs

Founded

2024

Country

Germany

Website

www.distillabs.ai/

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Alternatives

Alternatives

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