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Replicate's changelog

Agent skills for Replicate – Replicate changelog Fallback model for Nano Banana Pro – Replicate changelog MCP server auto-discovery – Replicate changelog Filter predictions by source – Replicate changelog The little things, week ending December 19, 2025 – Replicate changelog The little things, week ending December 5, 2025 – Replicate changelog The little things, week ending November 21, 2025 – Replicate changelog Code mode for Replicate's MCP server – Replicate changelog The little things, week ending November 7, 2025 – Replicate changelog Deployment setup monitoring – Replicate changelog The little things, week ending October 24, 2025 – Replicate changelog Set deadlines for predictions – Replicate changelog The little things, week ending October 10, 2025 – Replicate changelog Download invoices from billing settings – Replicate changelog Sort models by creation date via API – Replicate changelog Update model metadata via API – Replicate changelog The little things, week ending September 26, 2025 – Replicate changelog New search API, now in beta – Replicate changelog The little things, week ending September 12, 2025 – Replicate changelog Torch compile caching – Replicate changelog The little things, week ending August 29, 2025 – Replicate changelog The little things, week ending August 14, 2025 – Replicate changelog Run all models with the same API endpoint – Replicate changelog The little things, week ending August 1, 2025 – Replicate changelog Purchase prepaid credit – Replicate changelog Introducing a new Cog runtime – Replicate changelog The little things, week ending July 18, 2025 – Replicate changelog The little things, week ending July 4, 2025 – Replicate changelog Set a monthly spend limit deprecated – Replicate changelog See up to 24 hours of data on deployment metric graphs – Replicate changelog The little things, week ending June 20, 2025 – Replicate changelog Environment variables in running containers – Replicate changelog Slimmer API responses for model metadata – Replicate changelog The little things, week ending June 6, 2025 – Replicate changelog Faster, cheaper Flux training – Replicate changelog The little things, week ending May 23, 2025 – Replicate changelog Streaming text support in the playground – Replicate changelog Web URLs now in prediction objects – Replicate changelog Iterate in playground with audio support – Replicate changelog NVIDIA H100 GPUs now available – Replicate changelog More by this user – Replicate changelog The little things, week ending May 9, 2025 – Replicate changelog Copy docs directly to your LLM – Replicate changelog The little things, week ending April 25, 2025 – Replicate changelog The little things, week ending March 28, 2025 – Replicate changelog Simplified organizations – Replicate changelog The little things, week ending March 14, 2025 – Replicate changelog The little things, week ending February 28, 2025 – Replicate changelog Better prediction list – Replicate changelog The little things, week ending February 14, 2025 – Replicate changelog The little things, week ending January 31, 2025 – Replicate changelog Official models – Replicate changelog The little things, week ending January 17, 2025 – Replicate changelog The little things, week ending December 20, 2024 – Replicate changelog Language model training no longer supported – Replicate changelog GPU memory monitoring – Replicate changelog The little things, week ending December 06, 2024 – Replicate changelog The little things, week ending November 22, 2024 – Replicate changelog The little things, week ending November 8, 2024 – Replicate changelog A fond farewell to Python 3.7 – Replicate changelog The little things, week ending October 25, 2024 – Replicate changelog Dark mode – Replicate changelog Playground (beta) – Replicate changelog New documentation – Replicate changelog Synchronous API – Replicate changelog Large log outputs might be truncated – Replicate changelog Time limit for sharing predictions – Replicate changelog View training outputs on the web – Replicate changelog API for searching public models – Replicate changelog Streams always available, stream parameter deprecated – Replicate changelog Secret inputs for models – Replicate changelog Disable API tokens – Replicate changelog RSS and Atom feeds – Replicate changelog Delete stuff – Replicate changelog Docs and client library support for webhook verification – Replicate changelog Search for deployments – Replicate changelog Webhooks activity UI – Replicate changelog Improved validation for API prediction payloads – Replicate changelog T4 models now have more RAM – Replicate changelog GitHub secret scanning – Replicate changelog Bearer tokens – Replicate changelog Deployments API – Replicate changelog 3D viewer for GLB outputs – Replicate changelog Task-oriented collections – Replicate changelog Webhook verification – Replicate changelog Fine-tune SDXL from the web – Replicate changelog Compare image inputs to outputs – Replicate changelog Code snippets for every prediction – Replicate changelog API for creating models – Replicate changelog Improved training detail pages – Replicate changelog Prediction parameters as JSON – Replicate changelog API for listing public models – Replicate changelog Prediction query parameter – Replicate changelog Fullscreen training logs – Replicate changelog Dynamic status favicons – Replicate changelog Streaming output for language models – Replicate changelog Multiple API tokens for users – Replicate changelog A40 GPUs now available – Replicate changelog Hardware and pricing for trainable models – Replicate changelog Training API for language models – Replicate changelog
Deployments – Replicate changelog
2023-10-04 · via Replicate's changelog

You can now create a deployment to get more control over how your models run. Deployments allow you to run a model with a private, fixed API endpoint. You can configure the version of the model, the hardware it runs on, and how it scales.

Using deployments, you can:

  • Roll out new versions of your model without having to edit your code.
  • Keep instances always on to avoid cold boots.
  • Customize what hardware your models run on.
  • Monitor whether instances are booting up, running, or processing predictions.
  • View predictions that are flowing through your models.

Deployments work with both public models and your own private models.

🚀 Check out the deployments guide to learn more and get started.

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