FriendliAI

FriendliAI is a comprehensive generative AI infrastructure company dedicated to making the deployment and scaling of AI models effortless, fast, and cost-efficient. The platform provides a suite of tools designed to accelerate generative AI inference, enabling businesses to move from development to production seamlessly. By leveraging groundbreaking optimization technologies, FriendliAI significantly reduces operational costs and hardware requirements while boosting performance. It supports a vast ecosystem of over 400,000 models, including popular open-source LLMs like Llama, Mixtral, and Qwen, as well as custom and multimodal models.

The core of FriendliAI's offering is the Friendli Suite, which includes three main products tailored to different deployment needs: Friendli Dedicated Endpoints for guaranteed performance, Friendli Serverless Endpoints for pay-as-you-go flexibility, and Friendli Container for maximum security within a company's own infrastructure. The platform is built on proprietary technologies like Iteration Batching (Continuous Batching), optimized GPU kernels, and native quantization, which collectively deliver industry-leading throughput and low latency.

How to use FriendliAI

Getting started with FriendliAI is a straightforward process designed for developers and MLOps teams. Here’s a typical workflow:

1. Sign Up and Choose a Product: Create an account on the Friendli Suite. Depending on your needs, you can start with a free trial or credits. Choose between Dedicated Endpoints, Serverless Endpoints, or the Container solution.
2. Create a New Endpoint: In the dashboard, create a new project and then a new endpoint. Give it a unique name.
3. Select a Model: You can deploy models directly from popular repositories like Hugging Face or Weights & Biases (W&B). Simply provide the Model ID. Alternatively, you can upload your own custom-trained model.
4. Configure the Instance: Select the appropriate GPU instance type (e.g., A100, H100) based on your model's size and performance requirements. The platform provides suggestions to prevent VRAM issues.
5. Set Up Autoscaling: Configure autoscaling parameters to manage costs and performance effectively. You can set minimum and maximum replicas, with the ability to scale down to zero to eliminate costs during idle periods.
6. Deploy and Test: Click 'Create' to deploy the endpoint. Once initialized, you can use the built-in 'Playground' to send test prompts and verify the output.
7. Integrate with your Application: Use the provided API keys and code snippets (cURL, Python) to integrate the inference endpoint into your applications, products, or services.
8. Monitor and Optimize: Leverage the integrated dashboard to monitor endpoint performance, view logs, and analyze metrics to further optimize your deployment.

Core Features of FriendliAI

• Friendli Suite: An all-in-one platform with three deployment options: Dedicated Endpoints (guaranteed resources), Serverless Endpoints (pay-per-use), and Container (on-premise/VPC).
• Groundbreaking Performance: Utilizes proprietary technologies like Iteration Batching (Continuous Batching) to achieve up to 10.7x higher throughput and 6.2x lower latency compared to alternatives.
• Cost Efficiency: Delivers 50-90% cost savings by requiring up to 6x fewer GPUs for the same workload.
• Extensive Model Support: Seamlessly deploy over 400,000 models from Hugging Face, W&B, or upload custom models, including multimodal ones.
• Advanced Quantization: Supports native quantization techniques like FP8, INT8, and AWQ to serve models efficiently without compromising accuracy.
• Intelligent Autoscaling: Automatically adjusts resources based on real-time demand, including scaling to zero to minimize costs.
• AI Agent Building Tools: Features model-agnostic function calling, structured outputs, and integration with tools like web search and calculators to build reliable and complex AI agents.
• Production-Ready: Offers guaranteed SLAs, robust security for cloud or on-premise deployments, and advanced monitoring and debugging tools.

Use Cases for FriendliAI

FriendliAI is trusted by leading companies for demanding, production-grade AI applications.

• Large-Scale AI Services: Telecom providers like SKT use FriendliAI to power AI services for millions of users, achieving 5x higher throughput and 3x cost savings.
• High-Volume Chatbots: Companies like NextDay AI run personalized character chatbots processing over 3 trillion tokens per month, saving over 50% on GPU usage with Friendli Container.
• Enterprise AI Applications: Deploy custom-tuned models for specific business functions, such as internal knowledge base search, code generation, or customer support automation, with full data privacy using Friendli Container.
• Model Evaluation and Selection: Use the side-by-side comparison feature in Serverless Endpoints to evaluate and select the best-performing model for a specific use case.
• Building Complex AI Agents: Empower AI agents with external tools and reliable function calling to perform complex tasks like data analysis, booking systems, or automated workflows.

Advantages of FriendliAI

FriendliAI provides a distinct competitive edge through its focus on performance, cost, and flexibility. Its core advantage lies in its proprietary inference engine that dramatically outperforms other solutions. This leads to direct benefits such as significantly lower cloud computing bills and the ability to serve more users with less hardware. The platform's flexibility allows businesses to choose the perfect deployment model for their security and scaling needs, whether it's a fully-managed serverless API or a container running in their private cloud. The ease of use, with one-click deployments from Hugging Face and comprehensive monitoring tools, reduces the operational burden on engineering teams, allowing them to focus on building innovative AI products.

Pricing and Plans

FriendliAI offers a flexible, usage-based pricing model with a freemium entry point.

• Basic Plan: Get started with $5 in free credits. This plan is pay-as-you-go and provides access to core features like configurable autoscaling and deploying custom models.
• Enterprise Plan: Designed for large-scale deployments, this plan includes everything in Basic plus priority access to high-demand GPUs, advanced monitoring (Metrics & Logs), dedicated support, and custom pricing quotes.

Pricing for Friendli Dedicated Endpoints is billed per GPU hour, with rates varying by the type of GPU:

• A100 80GB: $2.9 / hour
• H100 80GB: $4.9 / hour
• H200 141GB: $5.9 / hour

Pricing for Friendli Container and Friendli Serverless Endpoints is also available and tailored to their specific usage patterns. Enterprise customers can contact sales for a customized, discounted pricing plan.