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Access powerful GPU clusters on-demand. Bittensor-validated quality. Per-second billing. 60% cheaper than hyperscalers.
A complete platform for running AI workloads at scale.
Drop-in replacement for OpenAI, Anthropic, and Cohere endpoints. Zero code changes — just swap your base URL.
Every provider is continuously benchmarked by Bittensor validators. Underperforming hardware is automatically deprioritized — cryptoeconomic incentives enforce quality.
SSH directly into dedicated GPU instances with root access. Install custom libraries, run arbitrary CUDA code, attach persistent storage.
Billed with per-second granularity. Run a 47-second test and pay for exactly 47 seconds. No rounding, no minimums, no surprises.
All inter-node traffic runs through WireGuard encrypted tunnels. Jobs execute in isolated Docker containers with zero shared GPU memory.
If a provider node drops mid-job, your workload migrates to an equivalent GPU with checkpoint recovery. Zero manual intervention.
from vexnode import VexNode
client = VexNode(api_key="your-key")
job = client.compute.create(
model="meta-llama/Llama-3-70B",
gpu_type="A100",
gpu_count=4,
script="train.py",
dataset="s3://my-bucket/data",
)
print(f"Job {job.id} running on {job.gpu_count}x {job.gpu_type}")Native support for the frameworks you already use.
Join the waitlist and get early access to VexNode GPU compute.