friendli.ai: Powering Scalable, High-Performance Generative AI Inference

friendli.ai is a cutting-edge generative AI inference platform built for production-scale deployment, empowering businesses and developers to run open-source and custom LLMs, multimodal models, and AI agents with unmatched speed, efficiency, and cost savings. Designed for seamless transition from prototype to real-world applications, it combines advanced optimization technologies with flexible deployment options to deliver sub-second latency, industry-leading throughput, and up to 90% cost reduction. With a strong focus on enterprise-grade reliability, security, and integration, friendli.ai supports a wide range of models from Hugging Face and enables rapid, scalable AI deployment across cloud, serverless, and private environments.

Key Features:

• Three Deployment Options: Friendli Dedicated Endpoints, Serverless Endpoints, and Friendli Container for flexible use cases.
• GPU-Optimized Serving: Patented Friendli Engine with Iteration Batching (Continuous Batching), Friendli DNN Library, Friendli TCache, and Native Quantization for peak performance.
• OpenAI Compatibility: Seamless integration with existing OpenAI workflows and tools.
• Support for 422,487+ Models: Access to a vast library of models from Hugging Face, including Llama 3.3 70B Instruct, DeepSeek R1, Qwen, Mixtral, Whisper, and more.
• Model Customization & Fine-Tuning: Full control over model configuration, versioning, and multi-LoRA deployments.
• Advanced Quantization: Supports FP8, INT8, and AWQ for faster, cheaper inference without sacrificing accuracy.
• Multimodal Inference: Enables efficient processing of text, image, audio, and video models with multimodal caching.
• Easy Integration: Official Python SDK (pip install friendli), API endpoints for chat completions and tool-assisted completions (Beta), and support for gRPC.
• One-Click Deployment: Deploy models directly from Hugging Face and Weights & Biases (W&B) with minimal setup.
• Autoscaling & SLA Guarantees: Dynamic resource scaling and service-level agreements for consistent performance.
• Private & On-Premise Deployment: Friendli Container allows full control via Docker, compatible with Kubernetes, Prometheus, Grafana, AWS EKS/SageMaker, and on-premise clusters.
• Free Credit Programs: Offers $5 free credits for new users and a limited $10,000 credit program for production-stage AI teams with instant onboarding and no long-term commitments.
• Enterprise-Grade Security & Compliance: Ideal for data-sensitive applications with secure, private, and auditable deployments.

Pricing: friendli.ai operates on a pay-as-you-go model based on GPU hours, with rates starting at $2.9/hour for A100 80GB, $4.9/hour for H100 80GB, and $5.9/hour for H200 141GB. Free credits are available for new users, and a $10K credit program is offered to teams deploying real inference at scale. Enterprise plans are available with custom pricing and include dedicated support, metrics & logs, endpoint versioning, and multi-LoRA capabilities.

Conclusion: With its powerful infrastructure, developer-friendly tools, and exceptional performance gains, friendli.ai is the ideal platform for teams ready to scale generative AI in production—offering speed, cost efficiency, and flexibility without compromise.