ZeroGPU is an edge inference cloud that turns idle compute from devices like phones, laptops, and gaming PCs into a distributed network for running AI workloads. It offers an OpenAI-compatible API, enabling developers to deploy small and nano language models at 50-70% lower cost than traditional GPU clouds, with up to 10x faster inference for specialized tasks. The platform includes a serverless model catalog, cloud fallback for reliability, and an agent storefront for autonomous AI purchasing.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional GPU cloud infrastructure is expensive and struggles to keep pace with surging AI inference demand, which is projected to grow from $106B to $255B by 2030. Most AI workloads, such as classification and content moderation, do not require frontier-level GPUs, yet companies still pay premium prices for unused capacity, while power and data-center buildout lag behind.
Solution
ZeroGPU provides an edge inference cloud that aggregates idle compute from devices like phones, laptops, and gaming PCs into a single programmable layer, turning them into a distributed inference network. The platform supports small and nano language models, including Qwen, DeepSeek, and Llama, alongside purpose-built ZLMs for tasks like content classification and intent extraction. Developers access the network via an OpenAI-compatible API, requiring only a base URL change, with automatic cloud fallback for burst capacity and reliability. ZeroGPU also offers a serverless model catalog with per-token pricing, and an agent storefront that lets AI agents purchase compute autonomously without signup, handling payments directly.
Target Audience
Primary customers are AI developers, startups, and enterprises running high-volume inference workloads like classification, summarization, and moderation, as well as Web3 teams and AI agents seeking low-cost, low-latency compute without managing GPU infrastructure.
Features
- Edge network of 100K+ devices running nano and small models, orchestrated via a lightweight SDK
- OpenAI-compatible API for drop-in integration with existing SDKs and one-line code changes
- Serverless model catalog with per-token pricing, including models like all-minilm-l6-v2 at $0.004 per 1M input tokens
- Purpose-built ZLMs for content classification, intent extraction, and moderation at production volume
- Cloud fallback to ensure consistent performance and handle burst workloads
- Agent storefront at agents.zerogpu.ai that publishes prices and payment instructions, enabling autonomous AI purchases without signup