Confidential and open LLM inference for agents, paid per request in USDC
Stage
Not given
Not given
Founded
Not given
Not given
Based in
Not given
US
Pricing model
Paid
Paid
Pricing
Not given
LLM inference: Models priced per million tokens input and output, ranging from $0.043 to $3.63 for input and $0.22 to $18.15 for output (e.g., Qwen3.8 27B route C: $0.043/$1.375, Kimi K3 route B: $3.63/$18.15). Virtual machines: Starter $0.159-$0.169/hour, Standard $0.318-$0.335/hour, Pro $0.636-$0.
Key features
Adapter registry with 191+ production-ready fine-tunes for discovery
In-browser A/B testing playground to compare adapters against base models
One-click deployment to serverless API endpoints with OpenAI-compatible format
Multi-adapter serving on single base model with zero cold starts
Automated fine-tuning with Unsloth-optimized kernels
Creator monetization with per-token revenue sharing
IP protection with managed endpoints and no public weight downloads
Framework integration as OpenAI-compatible proxy
Attested confidential model execution on Intel TDX hardware
Open tier LLM inference without attestation
Price shown before model execution
No account or API key required
Virtual machines for AI swarms by the hour
Phone numbers and calling with metered pricing
Email inboxes with sending allowances
Access via HTTP without signup
416 open source models available
What makes it different
2x-5x faster fine-tuning using Unsloth-optimized kernels compared to traditional methods
Creators earn 70% revenue share on every token served through their adapters
Encrypted memory and disk in processor with no company access to keys
Price transparent and settled before request execution
No account signup, payment via wallet address
Automatic enforcement of calling and messaging consent rules
AptAI
Agentgates