Replicate
by Replicate, Inc.
Run AI with an API
Cloud platform to run, fine-tune, and deploy open-source and custom machine learning models through a simple API, without managing GPU infrastructure.
Replicate is a cloud platform that lets developers run, fine-tune, and deploy machine learning models via a simple API. It hosts a large catalog of community-contributed, production-ready models (image, video, speech, music, and large language models) that can be called with minimal code. Developers can also package and deploy their own models using Cog, Replicate's open-source containerization tool, which generates an API server and manages the underlying cloud infrastructure. The platform auto-scales compute up and down with demand and bills per second of active usage. Founded in 2019 by Ben Firshman (creator of Docker Compose) and Andreas Jansson (ex-Spotify ML), Replicate went through Y Combinator (W20) and was acquired by Cloudflare (announced November 2025), continuing to operate as a distinct brand with its existing API.
At a Glance
- Category
- Infrastructure & Cloud
- Pricing
- Usage-based, Enterprise
- Target Market
- Enterprise, Startups, Developers
- Founded
- 2019
- Headquarters
- San Francisco, California, United States
Key Features
- ✓Run models via API
Access thousands of community-contributed, production-ready models (image, video, speech, music, and LLMs) and call them with as little as one line of code.
- ✓Cog
Open-source tool for packaging machine learning models into containers that automatically generates an API server and handles cloud infrastructure.
- ✓Fine-tuning
Customize existing models on your own data to create specialized versions for particular tasks.
- ✓Deployments & auto-scaling
Deploy your own models on dedicated hardware with automatic scaling up and down based on traffic, paying only for active compute.
- ✓Client SDKs
Official Python and JavaScript/Node.js client libraries for interacting with the platform programmatically.
- ✓Per-second usage billing
Transparent per-second GPU and CPU pricing (plus per-token/per-image rates for certain models) so you are billed only for what you use.
Capabilities
Use Cases
- •Add AI features to applications
Integrate image generation, video, speech, music, and language models into products through a single API without building ML infrastructure.
- •Deploy custom and fine-tuned models
Package models with Cog and deploy them to production with managed, auto-scaling GPU infrastructure.
- •Prototype and experiment with ML
Quickly test and iterate on open-source models in the cloud without provisioning or managing GPUs.
Ideal For
Best For
- ✓Developers integrating AI models into apps via API
- ✓Running open-source models without managing GPU infrastructure
- ✓Fine-tuning and deploying custom or proprietary models to production
Not Ideal For
- ✗Teams that require fully on-premise or air-gapped model hosting
Integrations
Deployment
Pricing
Pay-as-you-go (usage-based)
Per-second hardware billing, e.g. CPU $0.000100/sec (~$0.36/hr), Nvidia T4 $0.000225/sec (~$0.81/hr), Nvidia A100 80GB $0.001400/sec (~$5.04/hr), Nvidia H100 $0.001525/sec (~$5.49/hr); some models billed per token/per image (e.g. FLUX 1.1 Pro $0.04/image)
- ✓Billed by processing time on public models
- ✓Per-second GPU/CPU rates that scale with multi-GPU configs (2x/4x/8x)
- ✓Private/custom models billed for setup, idle, and active time
- ✓Official Python and JavaScript SDKs
Enterprise
Custom
- ✓Dedicated account manager
- ✓Priority support
- ✓Higher GPU limits
- ✓Performance SLAs
- ✓Volume discounts
Pricing is usage-based. Most public models are billed by processing time at per-second hardware rates that vary by GPU/CPU tier (e.g. CPU ~$0.36/hr, Nvidia T4 ~$0.81/hr, L40S ~$3.51/hr, A100 80GB ~$5.04/hr, H100 ~$5.49/hr), with multi-GPU options scaling proportionally. Certain models (notably large language models and some image models) are billed per input/output token or per output image instead of by time. Private/custom models run on dedicated hardware and are billed for setup, idle, and active processing time. Enterprise adds a dedicated account manager, priority support, higher GPU limits, performance SLAs, and volume discounts. Exact per-model rates are listed on each model page and on the pricing page.
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