All the latest open-source models are on Replicate. They’re not just demos — they all actually work and have production-ready APIs. AI shouldn’t be locked up inside academic papers and demos. Make it real by pushing it to Replicate.

This model costs approximately $0.025 to run on Replicate, or 40 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker. This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 26 …

Discover and share open-source machine learning models from the community that you can run in the cloud using Replicate.

Check out our docs for more information about how per-image pricing works on Replicate.

This model costs approximately $0.12 to run on Replicate, or 8 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker. This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 121 …

This model costs approximately $0.73 to run on Replicate, or 1 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker. This model runs on 4x Nvidia H100 GPU hardware. Predictions typically …

This goo was created with a model on Replicate: andreasjansson/plasma We’re bringing AI to every software developer. AI can do extraordinary things, but it’s still too hard to use.

This model costs approximately $0.0022 to run on Replicate, or 454 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker. This model runs on Nvidia T4 GPU hardware. Predictions typically …

This model costs approximately $0.0086 to run on Replicate, or 116 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker. This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 9 …

Replicate lets you run AI models with a cloud API, without having to understand machine learning or manage your own infrastructure. You can run open-source models that other people have published, bring your own training data to create fine-tuned models, or build and publish custom models from scratch.