How do parallel tool calls work?
mediumAnswer
- Modern APIs (OpenAI, Anthropic, Gemini) allow the model to emit multiple tool calls in a single assistant turn — e.g., 'call AND '.
- Runtime executes them concurrently, waits for both, appends both results, then re-invokes the LLM.
- Reduces latency for independent tools (network parallelism).
- Model has to be trained / prompted to emit them together — some models default to sequential.
- Trade-off: harder to debug + partial failures need explicit handling.
Check yourself — multiple choice
- Only sequential
- LLM emits multiple tool calls in one turn → run concurrently → append all results → re-invoke; reduces latency for independent tools
- Impossible
- Only for training
Parallel tool calls: multiple in one turn → concurrent execution → latency win.
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