Use Cases
Serverless GPU Inference
Deploy any AI model with lightning-fast cold starts. Scale automatically. Pay only for compute used.
Why Cumulus
Key Benefits
12.5s Cold Starts
4x faster than alternatives. Your models are ready to serve requests almost instantly, without waiting minutes for GPU provisioning.
Scale to Zero
When traffic drops, your deployment scales down to zero replicas — and zero cost. No more paying for idle GPUs sitting unused.
Any Model, Any Framework
Deploy LLMs, diffusion models, speech-to-text, computer vision, or any custom model. Cumulus is framework-agnostic and supports containerized workloads.
Process
Deploy in Three Steps
01
Write Your Model
Package your model using our Python SDK. Point to your model weights and define your inference function.
model.py
from cumulus import Model
class MyModel(Model):
def predict(self, input):
return self.model(input)
02
Deploy with One Command
deploy.py
# Deploy your model in one line
model = deploy("./my-model")
03
Call Your Endpoint
Get back a model_id and API endpoint. Call from any language.
terminal
# Call from anywhere
$ curl https://api.cumuluslabs.io/v1/predict \
-H "Authorization: Bearer $TOKEN" \
-d '{"model_id": "abc123"}'
Compatibility
Deploy Any Model
Large Language Models
- LLaMA
- Mistral
- Qwen
Image Generation
- Stable Diffusion
- Flux
- DALL-E
Speech & Audio
- Whisper
- TTS models
Computer Vision
- YOLO
- SAM
- CLIP
Custom Models
- PyTorch
- TensorFlow
- JAX