ModelRefs / Parallel Function Calling — Tool Pattern
Parallel Function Calling — Tool Pattern
Let the model emit multiple independent tool calls in one turn, execute them concurrently, and merge results.
Overview
When tool calls are independent the model can emit several in a single turn. The runtime executes them concurrently and feeds all results back before the next reasoning step.
When to use it: You need to reduce latency when several independent lookups satisfy the user request.
Pattern details
| Pattern class | function-calling |
|---|---|
| Difficulty | intermediate |
| Invocation mode | asynchronous |
| Also known as | multi-tool call, concurrent tool use |
| Last reviewed | 2026-06-07 |
Known failure modes
- Partial failure — Some tools succeed, others fail. Mitigation: Return per-call status and let the model reason over partial results.
- Rate-limit burst — Concurrent calls overflow upstream limits. Mitigation: Apply a concurrency cap and exponential backoff per tool.
When not to use it
- Treating dependent calls as parallel.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Parallel Function Calling — Tool Pattern.
Frequently asked questions
When should I use the Parallel Function Calling tool pattern?
You need to reduce latency when several independent lookups satisfy the user request.
What are common failure modes of Parallel Function Calling?
Partial failure • Rate-limit burst
Is Parallel Function Calling production-ready?
Yes when paired with the safety controls and observability hooks documented on the pattern page.