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@@ -235,7 +235,7 @@ DeepSeek-V3 can be deployed locally using the following hardware and open-source
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2. **SGLang**: Fully support the DeepSeek-V3 model in both BF16 and FP8 inference modes, with Multi-Token Prediction [coming soon](https://github.com/sgl-project/sglang/issues/2591).
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2. **SGLang**: Fully support the DeepSeek-V3 model in both BF16 and FP8 inference modes, with Multi-Token Prediction [coming soon](https://github.com/sgl-project/sglang/issues/2591).
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3. **LMDeploy**: Enables efficient FP8 and BF16 inference for local and cloud deployment.
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3. **LMDeploy**: Enables efficient FP8 and BF16 inference for local and cloud deployment.
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4. **TensorRT-LLM**: Currently supports BF16 inference and INT4/8 quantization, with FP8 support coming soon.
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4. **TensorRT-LLM**: Currently supports BF16 inference and INT4/8 quantization, with FP8 support coming soon.
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-5. **vLLM**: Support DeekSeek-V3 model with FP8 and BF16 modes for tensor parallelism and pipeline parallelism.
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+5. **vLLM**: Support DeepSeek-V3 model with FP8 and BF16 modes for tensor parallelism and pipeline parallelism.
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6. **AMD GPU**: Enables running the DeepSeek-V3 model on AMD GPUs via SGLang in both BF16 and FP8 modes.
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6. **AMD GPU**: Enables running the DeepSeek-V3 model on AMD GPUs via SGLang in both BF16 and FP8 modes.
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7. **Huawei Ascend NPU**: Supports running DeepSeek-V3 on Huawei Ascend devices.
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7. **Huawei Ascend NPU**: Supports running DeepSeek-V3 on Huawei Ascend devices.
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