Deep Infra

Pay-per-use APIs for fast, scalable AI model inference
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Deep Infra is a platform for deploying and running machine learning models through a straightforward API with pay-per-use pricing. It focuses on making inference fast, scalable, and production-ready, so teams can integrate state-of-the-art AI without managing complex GPU infrastructure. With Deep Infra, you can call popular models via a simple REST interface and get low-latency results for a range of workloads, from text generation to image creation.

The platform supports multiple model categories out of the box, including large language models for text generation (such as Llama and Qwen), text-to-speech models (including Kokoro and Dia), text-to-image models (such as Stable Diffusion and FLUX), and automatic speech recognition with models like Whisper. For teams that need more control, Deep Infra also allows deployment of custom LLMs on dedicated GPUs, making it suitable for proprietary models, fine-tuned checkpoints, or specialized latency and throughput requirements.

Getting started typically involves creating an account, installing the deepctl tool, selecting a model from the catalog, and then calling it from your application using the provided REST API. Deep Infra is designed for real production usage with scaling capabilities, including auto-scaling, so applications can handle changing traffic without manual intervention. This combination of accessible APIs, dedicated GPU options, and flexible usage-based billing makes it a practical choice for building and shipping AI-powered products quickly.

Review summary

Features

  • Fast inference with a simple REST API
  • Pay-per-use pricing
  • Low-latency, production-ready model serving
  • Scalable infrastructure with auto-scaling
  • Support for text generation (LLMs), text-to-speech, text-to-image, and ASR
  • Deploy custom LLMs on dedicated GPUs
  • Model catalog with popular architectures (e.g., Llama, Qwen, Stable Diffusion, FLUX, Whisper)

How It’s Used

  • Run text generation models for chat, summarization, and content creation
  • Generate speech from text for voice assistants and narration
  • Create images from text prompts for design and creative tools
  • Transcribe audio to text using ASR for meetings, support, and media
  • Deploy proprietary or fine-tuned LLMs on dedicated GPUs for controlled performance

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