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<p><a href="../zh/best_practices/DeepSeek-V3.md">简体中文</a></p>
<h1 id="deepseek-v3v31-model">DeepSeek-V3/V3.1 Model</h1>
<h2 id="i-environment-preparation">I. Environment Preparation</h2>
<h3 id="11-support-requirements">1.1 Support Requirements</h3>
<p>The minimum number of GPUs required for deployment on the following hardware for each quantization precision of DeepSeek-V3/V3.1 is as follows:</p>
<p>| | WINT4 |</p>
<p>|-----|-----|</p>
<p>|H800 80GB| 8 |</p>
<h3 id="12-installing-fastdeploy">1.2 Installing FastDeploy</h3>
<p>Refer to the installation process document <a href="../../get_started/installation/nvidia_gpu/">FastDeploy GPU Installation</a></p>
<h2 id="ii-how-to-use">II. How to Use</h2>
<h3 id="21-basics-starting-the-service">2.1 Basics: Starting the Service</h3>
<p><strong>Example 1:</strong> Deploying a Wint4 model with 16K context on an H800 with eight GPUs</p>
<pre><code class="language-shell">MODEL_PATH=/models/DeepSeek/DeepSeek-V3.1-Terminus-BF16
export FD_DISABLE_CHUNKED_PREFILL=1
export FD_ATTENTION_BACKEND=&quot;MLA_ATTN&quot;
export FLAGS_flash_attn_version=3
python -m fastdeploy.entrypoints.openai.api_server \
--model &quot;$MODEL_PATH&quot; \
--port 8180 \
--metrics-port 8181 \
--engine-worker-queue-port 8182 \
--cache-queue-port 8183 \
--tensor-parallel-size 8 \
--max-model-len 16384 \
--max-num-seq 100 \
--no-enable-prefix-caching \
--quantization wint4
</code></pre>
<p><strong>Example 2:</strong> Deploying a 16K context service for the block_wise_fp8 model on 16 cards on an H800</p>
<pre><code class="language-shell"># Currently only supports configurations with tp_size of 8 and ep_size of 16
MODEL_PATH=models/DeepSeek/DeepSeek-V3.1-Terminus-BF16
export FD_DISABLE_CHUNKED_PREFILL=1
export FD_ATTENTION_BACKEND=&quot;MLA_ATTN&quot;
export FLAGS_flash_attn_version=3
export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
export FD_ENABLE_MULTI_API_SERVER=1
python -m fastdeploy.entrypoints.openai.multi_api_server \
--ports &quot;9811&quot; \
--num-servers 1 \
--args --model &quot;$MODEL_PATH&quot; \
--ips &quot;10.95.247.24,10.95.244.147&quot; \
--no-enable-prefix-caching \
--quantization block_wise_fp8 \
--disable-sequence-parallel-moe \
--tensor-parallel-size 8 \
--num-gpu-blocks-override 1024 \
--data-parallel-size 2 \
--max-model-len 16384 \
--enable-expert-parallel \
--max-num-seqs 20 \
--graph-optimization-config '{&quot;use_cudagraph&quot;:true}'
</code></pre>
<p><strong>Example 3:</strong> Deploying a 16-card block_wise_fp8 model service with 16K contexts on an H800</p>
<p>This example supports MLA computation using the FlashMLA operator</p>
<pre><code class="language-shell">MODEL_PATH=models/DeepSeek/DeepSeek-V3.1-Terminus-BF16
export FD_DISABLE_CHUNKED_PREFILL=1
export FD_ATTENTION_BACKEND=&quot;MLA_ATTN&quot;
export FLAGS_flash_attn_version=3
export USE_FLASH_MLA=1
export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
export FD_ENABLE_MULTI_API_SERVER=1
python -m fastdeploy.entrypoints.openai.multi_api_server \
--ports &quot;9811,9812,9813,9814,9815,9816,9817,9818&quot; \
--num-servers 8 \
--args --model &quot;$MODEL_PATH&quot; \
--ips &quot;10.95.246.220,10.95.230.91&quot; \
--no-enable-prefix-caching \
--quantization block_wise_fp8 \
--disable-sequence-parallel-moe \
--tensor-parallel-size 1 \
--num-gpu-blocks-override 1024 \
--data-parallel-size 16 \
--max-model-len 16384 \
--enable-expert-parallel \
--max-num-seqs 20 \
--graph-optimization-config '{&quot;use_cudagraph&quot;:true}'
</code></pre>
<h1 id="deepseek-v32-model">DeepSeek-V3.2 Model</h1>
<h2 id="i-environment-preparation_1">I. Environment Preparation</h2>
<h3 id="11-support-requirements_1">1.1 Support Requirements</h3>
<p>The minimum number of GPUs required to deploy the DeepSeek-V3.2 model on the block_wise_fp8 platform under current quantization is as follows:</p>
<p>| | block_wise_fp8 |</p>
<p>|-----|-----|</p>
<p>|H800 80GB| 16 |</p>
<h3 id="12-installing-fastdeploy_1">1.2 Installing FastDeploy</h3>
<p>Refer to the installation process document <a href="../../get_started/installation/nvidia_gpu/">FastDeploy GPU Installation</a></p>
<h2 id="ii-how-to-use_1">II. How to Use</h2>
<h3 id="21-basics-starting-the-service_1">2.1 Basics: Starting the Service</h3>
<p><strong>Example 1:</strong> Deploying an 8K context service for the block_wise_fp8 model on a 16-GPU H800</p>
<pre><code class="language-shell">MODEL_PATH=/models/DeepSeek-V3.2-Exp-BF16
export FD_DISABLE_CHUNKED_PREFILL=1
export FD_ATTENTION_BACKEND=&quot;DSA_ATTN&quot;
export FD_ENABLE_MULTI_API_SERVER=1
python -m fastdeploy.entrypoints.openai.multi_api_server \
--ports &quot;8091,8092,8093,8094,8095,8096,8097,8098&quot; \
--num-servers 8 \
--args --model &quot;$MODEL_PATH&quot; \
--ips &quot;10.95.246.79,10.95.239.17&quot; \
--no-enable-prefix-caching \
--quantization block_wise_fp8 \
--disable-sequence-parallel-moe \
--tensor-parallel-size 1 \
--gpu-memory-utilization 0.85 \
--max-num-batched-tokens 8192 \
--data-parallel-size 16 \
--max-model-len 8192 \
--enable-expert-parallel \
--max-num-seqs 20 \
--num-gpu-blocks-override 2048 \
--graph-optimization-config '{&quot;use_cudagraph&quot;:false}' \
--no-enable-overlap-schedule
</code></pre>
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