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@@ -227,7 +227,7 @@ We also provide OpenAI-Compatible API at DeepSeek Platform: [platform.deepseek.c
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DeepSeek-V3 can be deployed locally using the following hardware and open-source community software:
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1. **DeepSeek-Infer Demo**: We provide a simple and lightweight demo for FP8 and BF16 inference.
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-2. **SGLang**: Fully support the DeepSeek-V3 model in both BF16 and FP8 inference modes.
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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.
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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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5. **vLLM**: Support DeekSeek-V3 model with FP8 and BF16 modes for tensor parallelism and pipeline parallelism.
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@@ -292,6 +292,8 @@ torchrun --nnodes 2 --nproc-per-node 8 generate.py --node-rank $RANK --master-ad
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Notably, [SGLang v0.4.1](https://github.com/sgl-project/sglang/releases/tag/v0.4.1) fully supports running DeepSeek-V3 on both **NVIDIA and AMD GPUs**, making it a highly versatile and robust solution.
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+SGLang also supports [multi-node tensor parallelism](https://github.com/sgl-project/sglang/tree/main/benchmark/deepseek_v3#example-serving-with-2-h208), enabling you to run this model on multiple network-connected machines.
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+
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Here are the launch instructions from the SGLang team: https://github.com/sgl-project/sglang/tree/main/benchmark/deepseek_v3
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### 6.3 Inference with LMDeploy (recommended)
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zhyncs