vLLM

Run open-weight LLMs locally with one command. OpenAI-compatible API.

The de-facto way to pull and run open-weight models (Llama, Qwen, Gemma, DeepSeek, gpt-oss) on your own machine — no API key, no data leaving the device. Ships native macOS/Windows/Linux apps, an OpenAI-compatible server, and official Python/JS libraries. MIT-licensed and free locally; an optional paid Ollama Cloud runs larger models.

Inference cloud for serving any AI model in production.

Production inference platform offering both pre-optimized Model APIs (Llama, DeepSeek, and more, billed per token) and dedicated GPU/CPU deployments for custom models, billed per minute with no charge for idle time. Custom models are packaged with its open-source Truss format and autoscale, including scale-to-zero. Aimed at low-latency, high-throughput serving.

Serverless GPUs. Run training, inference, batch jobs from Python.

Define cloud workloads in Python, deploy with one command — GPU access on demand, fast cold starts, fair-share pricing. The default 'I need to fine-tune a model from a Jupyter cell' platform.

Fast inference + fine-tuning. Production deployments at scale.

Optimized inference platform for open-weights models with strong latency numbers and serverless + dedicated deployment options. Fine-tuning supported; vision and audio models alongside text.