Focused model serving without per-token billing.
We lease dedicated bare-metal capacity, optimize it around a focused Qwen model offering, and sell predictable API access to developers and agent users.
What we operate
Yolo-Auto runs the model-serving stack rather than reselling a third-party model API. Requests may use infrastructure we own, lease, or rent, with Cloudflare and other service providers supporting networking, storage, security, and operations.
Why the model catalog is focused
Every additional model adds hardware fragmentation, scheduling complexity, idle capacity, and operational work. Concentrating on Qwen3.8-27B lets us tune the software and hardware around one primary workload while keeping the public API simple.
The current model is intended for chat, coding, technical documents, vision input, and agent workflows. We will add models only when we can support them without weakening the pricing and service approach.
How flat-rate access works economically
Dedicated capacity has a largely fixed operating cost. A focused serving stack, a small product surface, and direct infrastructure operation reduce the overhead that would otherwise be passed through as per-token charges.
Flat-rate does not mean infinite capacity. Paid plans include rolling workload allowances, workload-dependent agent capacity, bounded queues, and best-effort Shared Overflow. Those controls keep the service usable while the subscription bill remains predictable.
What customers should expect
Yolo-Auto is built for developers who want an OpenAI-compatible chat-completions endpoint, visible limits, minimal prompt retention, and a clear path from free integration testing to paid daily use.
We publish exact plan limits, model IDs, context windows, and rolling generation-speed estimates so customers can test the service against their own workloads before paying.