Run Any Replicate Model
replicate_run_modelRun any model from the Replicate catalog by its owner/name identifier. Supports all categories including embeddings, segmentation, depth estimation, and more.
Instructions
Generic escape hatch: run ANY model in the Replicate catalog by its "owner/name" identifier. This tool gives Claude access to the entire Replicate model catalog — anything not covered by the curated specialised tools (image, video, audio, speech, chat, vision, upscale, remove-bg) can be reached from here.
DISPLAY REQUIREMENT — if the result includes image URLs, paste ONE of the embed blocks the tool prints (iframe / / markdown — try in order) verbatim in your reply so the image renders inline in the chat.
Use this for any category WITHOUT a curated specialised tool, including but not limited to:
Embeddings (sentence-transformers, BGE, Jina)
Segmentation (SAM, Segment Anything)
Depth estimation (MiDaS, ZoeDepth, Marigold)
Inpainting / outpainting (LaMa, Stable Diffusion Inpaint, controlnet-inpaint)
ControlNet variants (canny, depth, openpose, normal-map)
Face / pose / hand detection (insightface, mediapipe, etc.)
3D generation (TripoSR, Wonder3D, InstantMesh)
Audio-to-text / speech recognition (whisper, Distil-Whisper)
Audio separation / stem splitting (Demucs, MDX)
Style transfer, colourisation, deblurring, denoising
Code completion / instruction-tuned code models (CodeLlama, DeepSeek-Coder)
Music continuation / source separation
ANY newly released model not yet in the curated registries
Workflow:
(Optional) Call replicate_search_models to discover models by keyword (e.g. "image segmentation", "speech to text").
(Recommended) Call replicate_get_model_schema with "owner/name" to inspect required inputs.
Call this tool with the model id and an input object matching that schema.
Args:
model (string): "owner/name" (latest official version) or "owner/name:version_hash" (pinned).
input (object): Model-specific input parameters.
download (boolean, default true): Download outputs locally.
timeout_ms: Default 300000.
Returns: PredictionResult.
Examples:
Upscale an image: model="nightmareai/real-esrgan", input={"image": "https://example.com/in.png", "scale": 4}
Remove background: model="lucataco/remove-bg", input={"image": ""}
Run an LLM (output is text, not a file, so local_paths will be empty): model="meta/meta-llama-3-70b-instruct", input={"prompt": "Explain quantum entanglement in two sentences."}
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | Model input parameters as a JSON object. Use replicate_get_model_schema first if unsure what a model accepts. | |
| model | Yes | Replicate model identifier. Either "owner/name" (uses latest official version) or "owner/name:version_hash" (pins a specific version). Examples: "black-forest-labs/flux-schnell", "meta/meta-llama-3-70b-instruct". | |
| download | No | Whether to download the generated files locally. Default true. When false, only Replicate URLs are returned (URLs expire after ~24h). | |
| timeout_ms | No | Max ms to wait for the prediction. If exceeded, returns the prediction ID so you can poll via replicate_get_prediction. Default: 300000 (5min). |