Deploy GPU applications on supported community hardware and cloud capacity
Pick your AI model based on evaluation results, not intuition
Stage
Startup
Not given
Founded
2026
Not given
Based in
SA
US
Pricing model
Paid
Not given
Pricing
One published price per GPU model in USD per GPU-hour. Hosts keep 90% of completed rental fees and Petabyte keeps 10%. A reservation holds funds, with final charges and returned balance following settlement after the run completes.
Not given
Key features
Choose from available GPU hardware with published hourly rates
Review cost estimates before deployment starts
Start from ready-made template applications
Monitor workload lifecycle states, logs and outputs
Connect your own GPU hardware as a host
Escrow-based payment system for secure transactions
Support for inference model requests
Automatic model routing based on evaluation results
GitHub repository integration for eval workflows
Stores evidence of evaluation results
Automatic re-evaluation when new models are released
Dashboard for monitoring routes
MCP server integration with ChatGPT, Claude, and Cursor
Configurable evaluation checks and criteria
What makes it different
Escrow payment ensures work is delivered before host is paid
Transparent pricing: all rates published upfront with no surprises
Minimal transaction fees: hosts keep 90% of rental earnings
Automatic refunds for failed rentals on platform side
Test your own LLM applications against real models automatically
Routes requests to the best-performing model in real time
Automatically updates routing when new models are released
Keeps your eval results and configurations under your control
BenchRouter