General Questions
What is Modelpilot.ai?
Modelpilot.ai is a platform that simplifies AI model deployment. It allows you to deploy state-of-the-art models with minimal technical knowledge, using either our recommended settings or custom configurations.
What types of models can I deploy?
You can deploy various types of models:
- Text Generation (LLMs like Mistral, Gemma, LLaMA)
- Image Generation (Stable Diffusion, Flux)
- Video Generation (Wan 2.1)
Do I need technical expertise to use Modelpilot?
No! That's the beauty of our platform. With our Quick Deploy feature, you can deploy sophisticated AI models with just a few clicks. No technical expertise is required for basic deployments.
How long does it take to deploy a model?
With Quick Deploy, you can start the deployment process in seconds. The actual deployment time varies by model:
- Text models: 5-10 minutes
- Image models: 7-12 minutes
- Video models: 10-15 minutes
Quick Deploy
What is Quick Deploy?
Quick Deploy is our one-click solution that automatically configures and launches models using our expert-recommended settings. It eliminates the technical complexities while ensuring optimal performance.
How does Quick Deploy work?
Our system analyzes your selected model's specific requirements and automatically selects the most appropriate instance type, memory allocation, storage volume sizes, and model-specific parameters. All you need to do is select a model and click "Deploy Recommended."
What makes Quick Deploy better than manual configuration?
- Time Efficiency: Deploy in seconds instead of minutes
- Reduced Complexity: No technical knowledge required
- Cost Optimization: Balance performance and price
- Error Prevention: Avoid common deployment mistakes
- Tested Configurations: Use settings proven to work reliably
When should I use Quick Deploy vs. Custom Deployment?
Use Quick Deploy when:
- You're new to model deployment
- You want the fastest deployment experience
- You trust our expert recommendations
- You don't have specific customization needs
Use Custom Deployment when:
- You need specific GPU types
- You require custom environment variables
- You need special network configurations
- You're integrating with existing infrastructure
- You have specific API settings beyond our defaults
Infrastructure & Hosting
What compute options are available?
We offer various instance types:
- CPU instances for smaller models
- GPU instances (L4, A6000, A100, H100) for larger models
- Custom configurations for specific needs
Can I use my own cloud account?
Yes, our Bring Your Own Cloud (BYOC) option allows you to use your own AWS, GCP, Azure, or RunPod account. This gives you complete control over your infrastructure while still benefiting from our deployment platform.
What is auto-scaling?
Auto-scaling automatically adjusts the number of replicas (instances) of your deployment based on load. This helps handle traffic spikes and reduce costs during periods of low usage.
Where are the models hosted?
Models are hosted in secure cloud environments. With managed hosting, we handle all the infrastructure. With BYOC, you can choose your preferred region and cloud provider.
Technical Questions
How do I access my deployed model?
Once deployed, you'll receive:
- A web interface URL (OpenWebUI for text models, ComfyUI for image/video models)
- An API endpoint for programmatic access
- Example API requests
Can I customize model parameters after deployment?
Most model parameters can be adjusted through the web interface or API requests. For fundamental changes to the deployment itself (like changing instance type), you'll need to create a new deployment.
What interfaces are provided for deployed models?
- Text models: OpenWebUI interface for chat and parameter adjustment
- Image/Video models: ComfyUI for workflow creation and visual output
- All models: RESTful API for programmatic access
How secure are my deployments?
All deployments include:
- Optional data encryption at rest
- API key authentication
- CORS configuration for web access control
- Private endpoint options
- Configurable data retention policies
Can I deploy models from Hugging Face?
Yes! You can deploy any model from Hugging Face by entering its model ID. Our system will recommend an appropriate instance type based on the model size, but you can customize this if needed.
Support & Troubleshooting
What if my deployment fails?
Common reasons for deployment failures include:
- Inadequate GPU memory for the selected model
- Resource availability in the selected region
- Network connectivity issues
The deployment logs will help identify the specific issue. You can try selecting a different instance type or region, or contact our support team for assistance.
How do I check deployment logs?
Deployment logs are available in your dashboard:
- Go to your deployments list
- Click on the specific deployment
- Navigate to the "Logs" tab
- You can view or download the logs for troubleshooting
How do I get support if I'm having issues?
We offer multiple support channels:
- In-app chat support
- Email support at support@modelpilot.ai
- Documentation and troubleshooting guides
- Community forums
Billing Related Questions
How does billing work?
We use a credit-based system where 1 credit = $1.00 USD. Credits are consumed based on the compute resources used, billed in 10-minute increments.
Why am I billed for a full 10 minutes even if I used less time?
Our platform bills in 10-minute increments to simplify accounting and optimize infrastructure provisioning. This is common practice for cloud computing resources.
How can I reduce my costs?
- Stop deployments when not in use
- Batch your work to maximize usage within each 10-minute billing increment
- Use appropriate instance types for your workloads
- Consider spot instances for non-critical workloads (up to 70% savings)
What happens if I run out of credits?
Running deployments will be automatically stopped when your credit balance reaches zero. To prevent service interruption, we recommend setting up a credit alert or enabling auto-recharge.