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DeepInfra

Freemium
ai infrastructureserverless gpumachine learningllm hostinginference apipay-as-you-godeveloper toolspaastext generationimage generation

DeepInfra offers a serverless platform for running AI models on production-grade GPUs, providing developers with high-speed inference and scalable infrastructure through a simple, pay-as-you-go, per-second billing API.

Try it out

DeepInfra is a managed infrastructure platform specializing in serverless GPU-powered AI inference. It allows developers to deploy and run a wide array of pre-optimized open-source AI models without managing complex hardware or scaling configurations. The primary audience consists of developers, ML engineers, and businesses needing to integrate scalable AI features, such as text generation or image creation, into their applications. Its core value proposition lies in its combination of high performance, including rapid cold starts, and a cost-effective pay-per-second pricing model which eliminates expenses for idle capacity. This focus on operational efficiency and developer experience makes it a strong choice for production AI workloads with variable traffic.

Pros

  • Pay-per-second pricing model minimizes costs by only charging for active compute time.
  • Serverless architecture automatically handles scaling from zero, eliminating infrastructure management overhead.
  • Extremely fast cold start times for many popular models, leading to better user experience.
  • Supports a wide and growing library of optimized, popular open-source models ready for immediate use.
  • Simple, unified REST API makes it easy to integrate inference into any application stack.

Cons

  • Primarily designed for inference workloads, not suitable for model training.
  • The model library is curated; running custom models requires building and hosting a specific Docker container.
  • Less control over the specific hardware environment compared to IaaS providers like AWS, GCP, or Azure.
  • Usage-based pricing can be difficult to predict and budget for applications with highly volatile traffic patterns.

Key features

  • Serverless GPU inference
  • Pay-per-second billing
  • Automatic scaling
  • Library of pre-optimized open-source models
  • REST API for inference
  • Support for custom models via Docker containers
  • Real-time performance metrics and logs
  • OpenAI compatible API endpoint

Integrations

Python Client LibraryJavaScript/TypeScript Client LibraryLangChainLlamaIndexOpenAI API compatible clientscURLREST API (language agnostic)

Target audience

AI application developers, ML engineers, and startups seeking to deploy scalable machine learning models for inference without managing underlying infrastructure.

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Founded

2021

Headquarters

San Francisco, USA

Pricing Tiers

Free Credits

New users receive $2 in free credits to experiment with the platform and run models.

Free

Pay-as-you-go

Pay per second of GPU usage. Pricing varies by the specific model and hardware it runs on. No monthly fees or idle costs.

Usage-based

Enterprise

Custom pricing for enterprise features, including dedicated capacity, private deployments, and volume discounts. Requires contacting sales.

Custom

Frequently Asked Questions

Top Alternatives to DeepInfra

Replicate

A developer might choose Replicate for its vast community-driven library of models and its ease of discovering and running new, experimental AI.

Together AI

Choose Together AI if your primary concern is the lowest possible cost-per-token for high-throughput inference or if you need to fine-tune open-source models.

AWS SageMaker Serverless Inference

An organization already heavily invested in the AWS ecosystem may prefer SageMaker for its deep integration with other AWS services and enterprise-grade security controls.

Anyscale

Choose Anyscale if you need a fully-managed platform built on Ray for scaling complex Python and AI workloads beyond just model inference.

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