A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 13, 15:45 UTC
[README] Add Arm CPUs to the list of supported targets (#28290)
Signed-off-by: Fadi Arafeh <fadi.arafeh@arm.com>
Fadi Arafeh committed
Nov 7, 2025 at 15:41 UTC
5fb4137c995a5b86153e63830970db7c568d1f89
2 files changed
+2
-2
README.md
+1
-1
@@ -84,7 +84,7 @@ vLLM is flexible and easy to use with:
84
- Tensor, pipeline, data and expert parallelism support for distributed inference
85
- Streaming outputs
86
- OpenAI-compatible API server
87
-- Support for NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs and GPUs, PowerPC CPUs, and TPU. Additionally, support for diverse hardware plugins such as Intel Gaudi, IBM Spyre and Huawei Ascend.
87
+- Support for NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs and GPUs, PowerPC CPUs, Arm CPUs, and TPU. Additionally, support for diverse hardware plugins such as Intel Gaudi, IBM Spyre and Huawei Ascend.
88
- Prefix caching support
89
- Multi-LoRA support
90
docs/README.md
+1
-1
@@ -56,7 +56,7 @@ vLLM is flexible and easy to use with:
56
- Tensor, pipeline, data and expert parallelism support for distributed inference
57
- Streaming outputs
58
- OpenAI-compatible API server
59
-- Support for NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs and GPUs, PowerPC CPUs, Arm CPUs and TPU. Additionally, support for diverse hardware plugins such as Intel Gaudi, IBM Spyre and Huawei Ascend.
59
+- Support for NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs and GPUs, PowerPC CPUs, Arm CPUs, and TPU. Additionally, support for diverse hardware plugins such as Intel Gaudi, IBM Spyre and Huawei Ascend.
60
- Prefix caching support
61
- Multi-LoRA support
62