# modal.concurrent | Modal Docs

- **URL:** https://modal.com/docs/reference/modal.concurrent
- **Summary:** Decorator that allows individual containers to handle multiple inputs concurrently.

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modal.concurrent
================

    concurrent(*, max_inputs=None, target_inputs=None)

Decorator that allows individual containers to handle multiple inputs concurrently.

The concurrency mechanism depends on whether the function is async or not:

*   Async functions will run inputs on a single thread as asyncio tasks.
*   Synchronous functions will use multi-threading. The code must be thread-safe.

Input concurrency will be most useful for workflows that are IO-bound (e.g., making network requests) or when running an inference server that supports dynamic batching.

When `target_inputs` is set, Modal’s autoscaler will try to provision resources such that each container is running that many inputs concurrently, rather than autoscaling based on `max_inputs`. Containers may burst up to up to `max_inputs` if resources are insufficient to remain at the target concurrency, e.g. when the arrival rate of inputs increases. This can trade-off a small increase in average latency to avoid larger tail latencies from input queuing.

_Added in v0.73.148:_ This decorator replaces the `allow_concurrent_inputs` parameter in `@app.function()` and `@app.cls()`.

**Usage**

    # Stack the decorator under `@app.function()` to enable input concurrency
    @app.function()
    @modal.concurrent(max_inputs=100)
    async def f(data):
        # Async function; will be scheduled as asyncio task
        ...
    
    # With `@app.cls()`, apply the decorator at the class level, not on individual methods
    @app.cls()
    @modal.concurrent(max_inputs=100, target_inputs=80)
    class C:
        @modal.method()
        def f(self, data):
            # Sync function; must be thread-safe
            ...

[modal.concurrent](https://modal.com/docs/reference/modal.concurrent#modalconcurrent)