Dedicated EndpointsBuild and run generative AI models on autopilot
Autopilot LLM endpoints for production
Easily create LLM inference endpoints that are performant, scalable, and cost-effective
Customer stories
SKT is South Korea's leading telecom operator known for its innovative mobile services, extensive 5G infrastructure and advancements in AI development.
Building and serving AI agents for SKT’s massive customer base required strict SLAs, high reliability, and the ability to efficiently handle heavy traffic.
Friendli Dedicated Endpoints enabled exceptional reliability and traffic efficiency while reducing operational costs.
Within
few hours of
onboarding
5×
LLM
throughput
3×
Cost
saving
Tunib's DearMate chatbot service offers various personas like friend, lover, counselor, and coach. Friendli Dedicated Endpoints' managed platform allows Tunib to focus on model training while automating GPU resource management and fault recovery.
Read moreFriendli Dedicated Endpoints simplifies generative AI model serving and optimizes our service development process.
Superior cost-efficiency and performance with Friendli Inference
Build and serve custom models
Efficient and cost-effective serving with autoscaling
Dedicated GPU resource management
We are excited to announce that FriendliAI has been officially recognized as an Amazon Web Services (AWS) Partner.
Now you can find Friendli Dedicated Endpoints on AWS marketplace, making building and serving LLMs seamless and efficient.
Superior cost-efficiency
and performance
A performant LLM serving solution is the first step to operating your AI application in the cloud.
Compared to vLLM, we boast:
token generation
initial response time
Run Friendli Inference on the cloud to reduce LLM serving cost up to 90%.
Our engine achieves 6 times higher throughput. Serve more traffic on fewer GPUs with Friendli Inference.
Our engine generates tokens 10 times faster to guarantee unmatched efficiency and performance in your generative AI operations.
Custom model support
We offer comprehensive support for both open-source and custom LLMs, allowing organizations to deploy models tailored to their unique requirements and domain-specific challenges.With the flexibility to integrate proprietary datasets, businesses can unlock new opportunities for innovation and differentiation in their AI-driven applications.Create a new endpoint with your private Hugging Face Model Hub repository or upload your model directly to Dedicated Endpoints.
Dedicated GPU Resource Management
Friendli Dedicated Endpoints provides dedicated GPU instances ensuring consistent access to computing resources without contention or performance fluctuations.By eliminating resource sharing, organizations can rely on predictable performance levels for their LLM inference tasks, enhancing productivity and reliability.
Multi-LoRA serving on a single GPU
With our specialized optimization, you can serve multiple LoRA models on a single endpoint using just one GPU. Streamline your operations and maximize resource efficiency.Enjoy greater flexibility and performance as you customize your models with enhanced access and efficiency. Optimize your deployments while maintaining top-tier performance.
Auto-scale your resources in the cloud
When deploying generative AI in the cloud, it’s important to scale as your business grows.Friendli Dedicated Endpoints employs intelligent auto-scaling mechanisms that dynamically adjust computing resources based on real-time demand and workload patterns.
Test your endpoints in the playground
Experiment with your model’s capabilities in the endpoint playground.Configure parameters like token length, temperature, top P, and frequency penalty.
Basic
Get $5 free creditsPay-as-you-go
Configurable autoscaling
Fine-tune custom models
Enterprise
Contact for custom pricingEverything in the Basic plan
Monitor endpoints with Metrics & Logs
Custom pricing
Pricing details
Endpoint
GPU Type
Basic
Enterprise
Read more from our blogs
- June 5, 2025
- 3 min read
One Click from W&B to FriendliAI: Deploy Models as Live Endpoints
- August 6, 2024
- 6 min read
Retrieval Augmented Generation (RAG) with MongoDB and FriendliAI
- June 20, 2024
- 4 min read
Deploying Weights & Biases Model Checkpoints on Friendli Dedicated Endpoints
Other ways to run generative AI models with Friendli
Friendli Container
Serve LLM and LMM inferences with Friendli Inference in your private environment
Learn more