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 14, 05:30 UTC
[DOC] update v1_guide with INTEL HW (#22679)
Signed-off-by: Chendi.Xue <chendi.xue@intel.com>
Chendi.Xue committed
Aug 12, 2025 at 03:22 UTC
59f3b936365afd200e474ddc9d1f5aa33f05b634
1 file changed
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docs/usage/v1_guide.md
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@@ -63,6 +63,7 @@ based on assigned priority, with FCFS as a tie-breaker), configurable via the
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|------------|-----------------------------------------------|
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| **NVIDIA** | <nobr>🚀</nobr> |
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| **AMD** | <nobr>🟢</nobr> |
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+| **INTEL GPU** | <nobr>🟢</nobr> |
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| **TPU** | <nobr>🟢</nobr> |
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| **CPU** | <nobr>🟢 (x86\_64/aarch64) 🟡 (MacOS) </nobr> |
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@@ -72,6 +73,7 @@ based on assigned priority, with FCFS as a tie-breaker), configurable via the
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- [vllm-ascend](https://github.com/vllm-project/vllm-ascend)
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- [vllm-spyre](https://github.com/vllm-project/vllm-spyre)
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+ - [vllm-gaudi](https://github.com/vllm-project/vllm-gaudi)
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- [vllm-openvino](https://github.com/vllm-project/vllm-openvino)
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Please check their corresponding repositories for more details.