vllm/docs/usage/reproducibility.md
Cyrus Leung 389aa1b2eb
[Doc] Update more docs with respect to V1 (#29188)
Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
2025-11-23 10:58:48 +08:00

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# Reproducibility
vLLM does not guarantee the reproducibility of the results by default, for the sake of performance. To achieve
reproducible results:
- In offline mode, you can either set `VLLM_ENABLE_V1_MULTIPROCESSING=0` which makes scheduling deterministic,
or enable [batch invariance](../features/batch_invariance.md) to make the outputs insensitive to scheduling.
- In online mode, you can only enable [batch invariance](../features/batch_invariance.md).
Example: [examples/offline_inference/reproducibility.py](../../examples/offline_inference/reproducibility.py)
!!! warning
Setting `VLLM_ENABLE_V1_MULTIPROCESSING=0` will change the random state of user code
(i.e. the code that constructs [LLM][vllm.LLM] class).
!!! note
Even with the above settings, vLLM only provides reproducibility
when it runs on the same hardware and the same vLLM version.
## Setting the global seed
The `seed` parameter in vLLM is used to control the random states for various random number generators.
If a specific seed value is provided, the random states for `random`, `np.random`, and `torch.manual_seed` will be set accordingly.
### Default Behavior
In V1, the `seed` parameter defaults to `0` which sets the random state for each worker, so the results will remain consistent for each vLLM run even if `temperature > 0`.
It is impossible to un-specify a seed for V1 because different workers need to sample the same outputs
for workflows such as speculative decoding. For more information, see: <https://github.com/vllm-project/vllm/pull/17929>
!!! note
The random state in user code (i.e. the code that constructs [LLM][vllm.LLM] class) is updated by vLLM
only if the workers are run in the same process as user code, i.e.: `VLLM_ENABLE_V1_MULTIPROCESSING=0`.
By default, `VLLM_ENABLE_V1_MULTIPROCESSING=1` so you can use vLLM without having to worry about
accidentally making deterministic subsequent operations that rely on random state.