Need whole nodes?
An endpoint and a node reservation serve different needs.
A dedicated endpoint serves your model. A reservation assigns whole GPU nodes to your account for a contracted term, for workspaces, serving and training.
What you get
Endpoints built for production
Dedicated capacity with the resilience and flexibility real workloads need.
Same unified API
Call your instance through the same OpenAI-compatible API as platform models — just address it with the model ID served_name:instance_id. No new base URL.
HuggingFace or custom containers
Deploy a managed vLLM server from any HuggingFace model, or bring your own container image and start command.
Multi-region routing
Run across regions and let the unified API route each request to a healthy one. As soon as a region is up, your endpoint is usable.
Multiple LoRA adapters
Serve many fine-tuned adapters on one instance and address each by its own alias (e.g. ft10:1) — no restart to add or swap them.
Sandboxed & isolated
Every instance runs in a security-hardened, network-isolated sandbox.
Adaptive scaling
Autoscaling adjusts capacity to live request volume. Pay per GPU-hour.
How you call it
One API, addressed by model ID
Your instance is reachable through the same endpoint as platform models. Set the model field to served_name:instance_id and keep your existing SDK.
from openai import OpenAI
client = OpenAI(
base_url="https://api.ecohash.com/v1",
api_key="eco_your_api_key",
)
# Address your instance with served_name:instance_id
response = client.chat.completions.create(
model="qwen3.5-35b-a3b:144",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)At a glance
The essentials
- Base URL
- api.ecohash.com/v1
- Model ID
- served_name:instance_id
- Billing
- Per GPU-hour