Inferless

Inferless provides serverless GPU infrastructure for deploying machine learning models at scale. The platform enables developers and teams to deploy any ML model—from Hugging Face, Git, Docker, or CLI—and get production-ready endpoints in minutes without managing GPU clusters or infrastructure. With automatic scaling from zero to hundreds of GPUs and per-second billing, Inferless eliminates idle costs while handling unpredictable workloads efficiently.

• Serverless GPU Deployment allows you to deploy models from Hugging Face, Git, Docker, or CLI with automatic redeploy options, getting from model file to endpoint in minutes without infrastructure setup.

• Auto-Scaling Infrastructure scales from zero to hundreds of GPUs automatically using an in-house built load balancer, handling spiky and unpredictable workloads with minimal overhead.

• Lightning-Fast Cold Starts delivers optimized model loading with sub-second responses even for large models, eliminating warm-up delays and wasted time.

• Custom Runtime Support lets you customize containers with the software and dependencies needed to run your specific models.

• NFS-like Volumes provides writable storage volumes that support simultaneous connections to various replicas for persistent data needs.

• Automated CI/CD enables auto-rebuild for models, eliminating the need for manual re-imports when code changes.

• Dynamic Batching increases throughput by enabling server-side request combining for better GPU utilization.

• Monitoring and Logging offers detailed call and build logs to monitor and refine models efficiently during development.

• Private Endpoints allows customization of endpoint settings including scale down, timeout, concurrency, testing, and webhook configurations.

• Enterprise Security includes SOC-2 Type II certification, penetration testing, regular vulnerability scans, and AES-256 encryption for model storage with complete isolation between customer environments.

To get started, sign up for a free account with $30 in credits (no credit card required), import your model from your preferred source, configure your GPU type (T4, A10, or A100), and deploy. The platform supports models up to 16GB with options for larger models through enterprise support.