Arrakis / Models / DeepSeek-V4-Pro

DeepSeek-V4-Pro GPU requirements

DeepSeek-V4-Pro has 1.6T parameters. To serve it, plan for about 3,837 GB of GPU memory in 16-bit, 1,919 GB in 8-bit or 959 GB in 4-bit, including about 20% for the KV cache and activations.

It is a mixture of experts: 384 experts, 6 of them active for each token. All of them stay in GPU memory, so plan memory for all 1.6T parameters.

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What it takes to serve it

GPU memory to run it for inference, with the smallest GPU setup that holds it and the lowest price on Arrakis right now.

Precision	Memory and the smallest setup
16-bit	3,837 GB: more than one 8-GPU machine
8-bit	1,919 GB: 8 × B300, from $36.80 per hour for all 8
4-bit	959 GB: 4 × B300, from $18.40 per hour for all 4

What it takes to fine-tune it

QLoRA trains adapters on a 4-bit frozen model, LoRA on a 16-bit one, and full fine-tuning updates every weight. Figures are before activations, which grow with batch size and sequence length.

Method	Memory and the smallest setup
QLoRA	1,119 GB: 8 × H200, from $32.24 per hour for all 8
LoRA	3,837 GB: more than one 8-GPU machine
Full fine-tuning	25,581 GB: more than one 8-GPU machine

About the model

From its card and files on Hugging Face. Memory figures here follow the GPU memory guide.

Parameters: 1.6T
Experts: 384
Experts for each token: 6
Context window (tokens): 1,048,576
Published in: FP8
License: mit
Released: 2026-04-22
Weights: deepseek-ai/DeepSeek-V4-Pro

Deploy it on Arrakis

Open Models in the console, choose vLLM, SGLang or llama.cpp, and rent a GPU it fits on. You get an OpenAI-compatible endpoint with its own API key, and root SSH to the machine. Or run it yourself on any machine with enough GPU memory:

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Questions

Live prices for every GPU are on the GPU prices page.

How much GPU memory does DeepSeek-V4-Pro need?

To serve it, about 3,837 GB in 16-bit, 1,919 GB in 8-bit, 959 GB in 4-bit, including about 20% for the KV cache and activations. To fine-tune it, about 1,119 GB with QLoRA, 3,837 GB with LoRA and 25,581 GB for full fine-tuning with Adam, before activations.

Can I run DeepSeek-V4-Pro on one GPU?

No. Even in 4-bit it needs about 959 GB: 4 B300 GPUs.

What does it cost to run DeepSeek-V4-Pro?

In 16-bit it needs more than one 8-GPU machine; in 4-bit, 4 B300 GPUs. Each setup on this page shows the lowest price per GPU-hour on Arrakis right now, and you pay by the hour from a prepaid balance.

How do I deploy DeepSeek-V4-Pro on Arrakis?

Open Models in the Arrakis console, paste deepseek-ai/DeepSeek-V4-Pro, choose vLLM, SGLang or llama.cpp, and rent a GPU it fits on. You get an OpenAI-compatible endpoint with its own API key, and root SSH to the machine.

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