Run lightweight inference at the edge.
Deploy optimized LLMs and ML models to edge servers. Sub-50ms inference with built-in model caching and automatic quantization.
LLM/Vision
Models
< 50 ms
Inference
On-premises
Data
GPU/NPU
Hardware
AI, locally.
Edge LLMs. Sub-50ms. Data sovereignty.
Edge LLMs
Run quantized LLMs (7B-70B) on edge servers with GPU.
Sub-50ms inference
Optimized runtime with model caching for fast inference.
Data sovereignty
Data never leaves your premises. Fully on-site processing.
Auto-quantization
Automatically quantize models for edge hardware.
Model serving
OpenAI-compatible API for drop-in replacement.
Hybrid fallback
Automatic cloud fallback for complex queries.
Getting started
Launch your first instance in three steps. CLI, console, or API — your choice.
ur edge ai endpoint create \
--model=llama-3-8b-q4 \
--server=edge-srv-01Local AI patterns.
Private LLM and retail edge AI.
Suggested configuration
Edge · Data sovereignty · GPU
Estimate your costs
Create detailed configurations to see exactly how much your architecture will cost. Pay for what you use, down to the second.
Configuration 1
Edge AI Deployment
Usage Volume
Infrastructure
Options
Cost details
Sub-50ms local inference. Model caching and quantization.
Works seamlessly with
Frequently asked questions
AI, locally.
Edge LLMs. Sub-50ms. Data sovereignty.