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  ## Inference Performance
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- This model achieves up to 1.6x speedup in single-stream deployment and up to 1.7x speedup in multi-stream asynchronous deployment, depending on hardware and use-case scenario.
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  The following performance benchmarks were conducted with [vLLM](https://docs.vllm.ai/en/latest/) version 0.6.6.post1, and [GuideLLM](https://github.com/neuralmagic/guidellm).
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  ### Single-stream performance (measured with vLLM version 0.6.6.post1)
 
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  ## Inference Performance
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+ This model achieves up to 2.7x speedup in single-stream deployment and up to 1.5x speedup in multi-stream asynchronous deployment, depending on hardware and use-case scenario.
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  The following performance benchmarks were conducted with [vLLM](https://docs.vllm.ai/en/latest/) version 0.6.6.post1, and [GuideLLM](https://github.com/neuralmagic/guidellm).
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  ### Single-stream performance (measured with vLLM version 0.6.6.post1)