- Shared GPU Resources: Our platform enables multiple models and workloads to share GPUs, with automatic rebalancing and node draining to ensure optimized utilization and cost reduction.
- Advanced Integrations: One of our standout features is the seamless model import from your favorite repositories, including Huggingface, AWS Sagemaker, Google Vertex AI, and Github, all with just a single click. Stay tuned for our upcoming integration with Azure!
- Scalable Deployment: Inferless offers auto-scaling based on requests per second, allowing you to scale from zero to thousands of GPUs seamlessly.
- Computation Type Support: We support various computation types, including deep learning models from major ML frameworks like Pytorch, Tensorflow, ONNX, and even custom Python functions.
- Dynamic Model Registration and Versioning: You can easily register new models or versions using CI/CD pipelines without having to rebuild or redeploy the infrastructure.
- API Endpoints: Obtain ready-to-use API endpoints that can be effortlessly integrated into your backend or front-end applications.
- Advanced Monitoring Capabilities: Inferless comes with built-in Prometheus metrics and Grafana dashboards for visualizing GPU usage and other system metrics.
- Low GPU Utilization: With Inferless Serverless Offering, you no longer need to worry about the costs associated with underutilized GPUs, as you only pay for what you use.
- High Maintenance: Setting up Inferless is a breeze, and it provides you with an Endpoint API for your model, eliminating the need for in-depth DevOps knowledge.
- Tackling Latency Challenges: Our custom-built orchestration engine, advanced router, and proprietary storage infrastructure work in tandem to help you achieve the desired latency results for your applications.
- Stress-Free Hardware Provisioning: We have pre-provisioned hundreds of GPUs to save you from dealing with quotas and hardware management, allowing you to focus on your core tasks.