Introduction

Common Compute is a distributed network for batch AI workloads. You ship tasks — embeddings, transcription, OCR, reranking — and get back deterministic quotes before any GPU runs. Tasks execute in sandboxed containers on idle Apple Silicon across thousands of machines.

This guide walks you from install to your first production job in under ten minutes. If you already have an OpenAI, Cohere, or AWS Transcribe integration, you can port in a single line change.

What this is good for

• High-volume batch inference where seconds of latency is acceptable
• Workloads that dominate your AI bill today
• Pipelines with deterministic compute needs and tolerances for retries

What this is not good for

• Sub-100ms realtime inference (use your existing provider)
• Training large models (we dispatch inference only)
• Stateful, long-running processes (tasks are bounded)