Host Llama-3 8B
on your own GPU VMs.
Host Llama-3 8B on entry-level GPU hardware for cheap, private text inference.
Llama-3 8B Overview & Capabilities
A highly efficient, lightweight model suitable for edge hosting, single-GPU setups, fast text completion, and focused classification tasks.
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: 8 Billion
- Minimum recommended VRAM: 16 GB
- Recommended GPU Layout: 1x NVIDIA T4 (16GB) or 1x NVIDIA A10G (24GB)
- Suggested Cloud Instance: g5.xlarge (AWS) or n1-standard-4 + T4 (GCP) (Meta AI 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 llama-3-8b \
--cloud aws --region us-east-1 \
--instance-type g5.xlarge \
--gpu-count 1 \
--engine ollama \
--enable-ssl --domain llama8b.example.comLlama-3 8B Hosting FAQ
Deploy Llama-3 8B now
Experience secure, private, and fast text generation on your own cloud nodes.