Private Model Deployment
Custom Chutes:Your Model. Your Compute. Your API.
Deploy private models for production without running platform infrastructure yourself. Chutes gives your team a secure path to deploy private AI model workloads and ship custom AI inference endpoints quickly.
Prefer docs first? Read the Custom Chutes guide.
Built for high-trust AI use cases
Private Fine-Tunes
Deploy internal fine-tuned LLMs with private access controls for teams that cannot expose model weights publicly.
Proprietary Weights
Run closed-source or licensed models on dedicated infrastructure so your weights and prompts stay in your own boundary.
Compliance-Sensitive Workloads
Build HIPAA and enterprise workflows with isolated execution and auditable model access policies.
Internal Tooling
Power copilots, retrieval workflows, and automation tools for your company with custom AI inference endpoints.
How it works
A simple 3-step flow from upload to production API.
01
Upload Your Model
Bring your model artifacts, dependencies, and runtime config using the Chutes SDK or template workflows.
02
Deploy Your Chute
Launch private model infrastructure with your own quotas, access controls, and performance settings.
03
Call Your API
Get a dedicated endpoint and integrate immediately from your app, backend jobs, and internal services.
Custom chute features
- Private access controls for every deployment
- No shared GPU requirement for dedicated workloads
- Custom quotas and request governance
- Dedicated onboarding and enterprise support
Pricing
Enterprise and advanced custom deployments are scoped per workload. Share your use case and we will build a tailored pricing plan.
Contact us for enterprise pricing, deployment guidance, and migration support.