Best GPU for DeepSeek Coder V2 (2025)

DeepSeek Coder V2 is a favorite among developers. Its Mixture-of-Experts (MoE) architecture is efficient but still demands 16GB+ VRAM for smooth code generation and large context windows.

Prices updated: Dec 5, 2025

Minimum VRAM 16 GB

Recommended 24 GB+

BEST PERFORMANCE

GeForce RTX 5090

32GB GDDR7

The ultimate choice for DeepSeek Coder V2. With 32GB GDDR7 VRAM and a massive score of 14,480, it handles large contexts and training with ease.

$3199.99 Buy on Amazon

BEST VALUE

Radeon RX 9060 XT 8 GB

8GB GDDR6

The smart choice. It meets the 16GB requirement perfectly while offering the best performance per dollar ratio.

$287.99 Buy on Amazon

BUDGET PICK

GeForce RTX 3050 8 GB

8GB GDDR6

The most affordable way to run DeepSeek Coder V2. It hits the minimum specs needed to get started without breaking the bank.

$209.99 Buy on Amazon

Why VRAM Matters for DeepSeek Coder V2

DeepSeek Coder V2 uses a Mixture-of-Experts (MoE) architecture. While it activates fewer parameters per token, the total model size is still large. More importantly, coding tasks often require massive context windows (reading entire files or repositories). A 16GB card allows for decent context, but 24GB is preferred to utilize the model's long-context capabilities without hitting OOM errors during complex refactoring tasks.

DeepSeek Coder V2 GPU & System Requirements

CPU

Modern 8-core CPU

RAM

32GB or 64GB (Coding tasks often involve IDEs and Docker running alongside)

Storage

NVMe SSD

All Compatible GPUs for DeepSeek Coder V2

GPU	Steel Nomad ↓	Price ↕	VRAM ↕	Bandwidth	Release Date ↕	Cores
GeForce RTX 5090	14,480	$3199.99	32GB GDDR7	1790 GB/s	Jan 30th, 2025	21,760
GeForce RTX 4090	9,236	$3134.99	24GB GDDR6X	1010 GB/s	Sep 20th, 2022	16,384
GeForce RTX 5080	8,762	$999.99	16GB GDDR7	960 GB/s	Jan 30th, 2025	10,752
Radeon RX 9070 XT	7,249	$629.99	16GB GDDR6	644 GB/s	Mar 6th, 2025	4,096
Radeon RX 7900 XTX	6,837	$580.61	24GB GDDR6	960 GB/s	Nov 3rd, 2022	6,144

Frequently Asked Questions

What are the recommended GPU requirements for DeepSeek Coder V2?

For the standard 16B/236B MoE model, we recommend at least 16GB VRAM for basic usage. However, to fully utilize its long context window for coding projects, 24GB VRAM (RTX 3090/4090) is the ideal requirement.

Is 16GB VRAM enough for DeepSeek Coder V2?

For the 'Lite' versions or heavily quantized standard versions, yes. However, if you want to use the larger 236B MoE model, you will need significantly more VRAM (often multi-GPU setups similar to Llama 3 70B).

Does CUDA core count matter for coding?

Yes, but VRAM is the bottleneck. Once the model fits in VRAM, generation speed (tokens per second) scales with memory bandwidth and compute. An RTX 4090 will be much snappier than a 3090, which makes the coding assistant feel more 'real-time'.