Host FLUX.1 Schnell
on your own GPU VMs.
Deploy FLUX.1 image generators to private GPU instances without per-image subscription markups.
FLUX.1 Schnell Overview & Capabilities
State-of-the-art open image generation model producing incredible detail, text rendering, and instruction following in 4 step inference cycles.
Optimized GPU Kernels
vxcloud packages models with highly optimized vLLM or Ollama layers, yielding maximum token-generation speed.
100% Data Privacy
Run inference within your own VPC boundary. No queries, training prompts, or logs flow to third-party endpoints.
OpenAI-Compatible APIs
Exposes standardized endpoints, allowing you to drop your private backend straight into existing LangChain/LlamaIndex code.
Quantized Weights support
Supports AWQ and GPTQ quantization out of the box, reducing GPU VRAM memory targets by up to 75%.
Dynamic Scaling
Spin up additional replica VMs behind load balancers to distribute high-volume client completions.
Flat Compute Costs
Ditch per-token query markups. You only pay for the VM run hours directly, cutting API expenses at scale.
Deployment Hardware Specifications
AI models demand heavy GPU memory profiles. Review these suggested minimum configurations to prevent Out-Of-Memory compilation failures.
- Model Parameters: 12 Billion (distilled)
- Minimum recommended VRAM: 24 GB
- Recommended GPU Layout: 1x NVIDIA A10G (24GB) or 1x NVIDIA L4 (24GB)
- Suggested Cloud Instance: g5.2xlarge (AWS) or g2-standard-8 (GCP) (Black Forest Labs optimized)
One-Command GPU Deployment Setup
Run this command inside your terminal session to provision GPU resources and deploy the OpenAI-compatible vLLM API layer.
vxcli deploy model flux-schnell \
--cloud aws --region us-east-1 \
--instance-type g5.2xlarge \
--gpu-count 1 \
--engine diffusers-api \
--enable-ssl --domain flux.example.comFLUX.1 Schnell Hosting FAQ
Deploy FLUX.1 Schnell now
Experience secure, private, and fast text generation on your own cloud nodes.