DeepSeek V3 is an open-source AI model developed by DeepSeek. It can be deployed on-premises with the right GPU hardware for private, secure AI inference.

How much VRAM does DeepSeek V3 require?

VRAM requirements for DeepSeek V3 depend on the quantization level. Full-precision models need more VRAM, while quantized versions (Q4, Q5, Q8) can run on consumer GPUs. See our VRAM requirements table for specific recommendations.

Can I run DeepSeek V3 locally?

Yes. DeepSeek V3 can be run locally using frameworks like Ollama or vLLM. Petronella Technology Group builds GPU-accelerated workstations and servers optimized for local AI model deployment.

What GPU do I need for DeepSeek V3?

The recommended GPU depends on the model size and quantization. For smaller quantized versions, an AMD Radeon or NVIDIA RTX GPU with 16-24 GB VRAM may suffice. For full-precision or larger variants, enterprise GPUs like the AMD Instinct MI300X or NVIDIA A100 are recommended.

Does Petronella help deploy DeepSeek V3?

Yes. Petronella Technology Group provides end-to-end AI deployment services including hardware selection, system configuration, model optimization, and ongoing support. Contact us to discuss your DeepSeek V3 deployment needs.

Open-Source AI Model

DeepSeek V3

Name: DeepSeek V3
Author: DeepSeek

Developed by DeepSeek

Local AI Deployment Experts 24+ Years IT Infrastructure GPU Hardware In Stock

Key Capabilities

GPT-4 class performance at open-source level
Highly efficient MoE - only 37B parameters active per token
128K context window
Strong math, coding, and Chinese language capabilities
Multi-head Latent Attention reduces KV cache by 93%

VRAM Requirements by Quantization

Choose the right GPU based on your performance and quality needs.

Model / Quantization	VRAM Required
full FP16	1.3TB+
Q4	350GB
Q2	170GB

Use Cases

DeepSeek V3 (671B total (37B active via MoE)) can be deployed for enterprise AI applications including document processing, code generation, data analysis, and conversational AI. License: MIT License.

Run DeepSeek V3 with Petronella

PTG builds DeepSeek V3 inference clusters that deliver GPT-4 class performance with zero API costs. The MIT license and MoE efficiency make it the most cost-effective frontier model to self-host.

Recommended Hardware

Model Size	Recommended GPU
full FP16	DGX B300 (2.3TB HBM3e) or multi-node cluster
Q4 quantized	DGX Station GB300 (384GB) or 4x RTX PRO 6000 (384GB)
Q2 quantized	DGX Spark (128GB) or 2x RTX PRO 6000 (192GB)

Deploy DeepSeek V3 On-Premises

Our team builds GPU-accelerated systems configured and optimized for DeepSeek V3. Private, secure, and fully under your control.

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DeepSeek V3

⚡Key Capabilities

📌VRAM Requirements by Quantization

🚀Use Cases