Start Async Batch Predictions
replicate_batch_startRun up to 50 Replicate predictions in parallel without blocking. Receive a job ID instantly and poll for progress and results.
Instructions
Run multiple Replicate predictions in parallel as a background job. Returns a job_id immediately — the predictions run in the background. Poll replicate_batch_status for progress and results.
Use this when you have 2–50 predictions to run and don't want to block. Each item specifies its own model and input, so you can mix models in one batch.
IMPORTANT: model must be a full Replicate identifier ("owner/name" or "owner/name:version"), not a curated shortcut like "flux-schnell". Use replicate_get_model_schema to look up the correct identifier.
Args:
items (array, 1–50): Predictions to run. Each: { model: "owner/name[:version]", input: {...} }.
concurrency (1–10, default 3): Max simultaneous predictions. Raise with caution — Replicate rate-limits free accounts.
download (boolean, default true): Download output files locally.
timeout_ms_per_item (default 300000): Per-prediction timeout. Timed-out items have pending=true in their result.
ttl_hours (1–72, default 1): How long to keep results in memory. Job state is lost if the MCP server restarts.
Returns: { job_id, total, message }
Example: items=[ { model: "black-forest-labs/flux-schnell", input: { prompt: "a red fox" } }, { model: "black-forest-labs/flux-schnell", input: { prompt: "a blue whale" } }, ] → Returns { job_id: "abc-123", total: 2, message: "..." } → Then poll: replicate_batch_status({ job_id: "abc-123" })
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Predictions to run. 1–50 items. | |
| download | No | Download output files locally. Default: true. | |
| ttl_hours | No | How long to keep job results in memory (1–72h). Default: 1h. State is lost if the server restarts. | |
| concurrency | No | Max simultaneous predictions (1–10). Default: 3. | |
| timeout_ms_per_item | No | Per-prediction timeout in ms (5000–1800000). Default: 300000 (5min). |