AI/ML Model Hosting & Inference Platforms

These platforms are purpose-built for serving machine learning models via APIs, providing GPU-backed infrastructure, pre-configured runtimes, and integration with ML frameworks like PyTorch, TensorFlow, and scikit-learn. They’re ideal for forum users creating AI demos, deploying inference endpoints, or experimenting with LLMs. Most offer usage-based billing, so you only pay for compute time. Many platforms support running models using Gradio or Streamlit, making them perfect for sharing public or internal ML apps.

Tools:

• Hugging Face Spaces – Hosts ML demos using Gradio or Streamlit, with GPU support and community sharing. Ideal for showcasing models, notebooks, and NLP pipelines.

• Replicate – Allows you to run and deploy ML models as APIs from GitHub or custom training. You’re charged only for the time your model runs.

• Modal – A serverless platform for running Python scripts and ML models with Docker-like simplicity. Supports custom environments, APIs, and background tasks for inference pipelines.

• Banana.dev – GPU-based inference hosting for deploying deep learning models as scalable APIs. Great for computer vision, LLMs, and generative models with real-time latency.