Fastest, most efficient inference for fine-tuned LLMs
Serve 100s of small fine-tuned models on a single GPU at speeds 2-3x faster than other solutions. Powered by LoRAX and Turbo LoRA.
Serving Infra Built For Your Needs
We offer deployment methods designed for teams at any stage of development from early experimentation through large-scale production.
Shared Serverless
Use our endpoints to get started fast. Great for experimenting with different base models and fine-tuned adapters.
Private Serverless
Automatically spin up a private, serverless GPU deployment for any base model and serve 100s of fine-tuned models on top using LoRAX.
Virtual Private Cloud
Use your own cloud environment for complete control and the strictest privacy and security.
Faster And More Cost-Effective Inference
Low latency enables real-time interactive applications
High throughput supports more simultaneous requests
Cost efficiency that scales with your AI initiatives
Fast, Efficient Deployments Powered by LoRAX’s Innovations
LoRA eXchange (LoRAX) enables you to serve hundreds of fine-tuned LLMs from a single GPU without sacrificing performance, saving you significant cost and resources.
Continuous Multi-Adapter Batching
Load multiple adapters on a single GPU deployment in a single model forward pass with nearly no impact on latency.
Tiered Weight Caching
Automatically unload unused adapters from GPU to CPU to disk to avoid out-of-memory errors.
Dynamic Adapter Loading
Each set of fine-tuned LoRA weights is loaded from storage just-in-time as requests come in at runtime, without blocking concurrent requests.
Manage Your Instance Through an Intuitive UI
Custom Autoscaling Compute
Automatically suspend GPUs if a deployment doesn’t receive requests for a specified amount of time or enter 0 for an always-on deployment.
Manage Deployments in One Place
Get a bird’s eye view of your private serverless and shared serverless deployments. Create new deployments with just a few clicks or a few lines of code.
Choose your GPUs
Optimize for cost and performance by specifying a GPU for the deployment.
View a detailed event log
Dive into a full event log to diagnose errors
