start_batch
shallowstudio.ai3d/ai3d-studio · Verify this server
Run the same model, scene and options once for each of several pictures in the account’s Library — for example image to 3D for twelve product photos. Take the scenes and models from list_models (`batches`), and each picture’s asset_id from get_job or search_library on a finished image job. Nothing is charged now: each run is charged as it starts and refunded if it fails, but the balance must cover the whole quote, and for a key or connection with a monthly limit the whole quote is held against it until each picture runs (then its real cost counts) or is cancelled, refused or refunded (then nothing does). Returns a batch id at once; follow it with get_batch. Pass idempotency_key on retries so a repeat returns the same batch instead of queueing another.
1 trials · measured today
start_batch scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against studio.ai3d/ai3d-studio, measured 20 Oct 2026 under methodology v0.2.0. Every measured component scored 100.
Component breakdown
| Component | Weight | Value |
|---|---|---|
| Reliability | 35% | not applicable |
| Schema integrity | 25% | 100.0 |
| Failure behaviour | 15% | not applicable |
| Latency | 15% | not applicable |
| Concurrency | 10% | not applicable |
Tool details
- Transport
- remote
- Credential class
- self-provisionable
- Input schema
- not declared
- Output schema
- not declared
- Side-effect classification
- unclassified
Score history
| Day | Score | Tier | Methodology |
|---|---|---|---|
| 2026-10-20 | 100.0 | shallow | v0.2.0 |
Probe evidence
| Probe | Outcomes |
|---|---|
| schema_integrity | pass: 1 |
Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.
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