Can RTX 3080 Ti run Qwen 2.5 Coder 7B?

Yes — runs locally

~46 tok/sec · Fast — smooth conversation. Responses feel real-time.

Your VRAM

12 GB

Model size

7.6B

Best quant

Q4_K_M

VRAM needed

4.9 GB

The verdict

The RTX 3080 Ti (12 GB VRAM) handles Qwen 2.5 Coder 7B comfortably using the Q4_K_M quantization, which fits in 4.9 GB. Expected throughput is around 46 tokens/second, which feels Fast — smooth conversation. Responses feel real-time. in interactive use. Strong 7B code model rivaling larger coding models. Excellent for local development.

Setup tutorial: Qwen 2.5 Coder 7B on RTX 3080 Ti

AI-generated, GPU-specific. Verified commands for your exact hardware.

TL;DR

Run Qwen 2.5 Coder 7B on your NVIDIA GeForce RTX 3080 Ti with Grade S performance at ~102 tok/sec using the Q4_K_M quantization.

Prerequisites

Before starting, ensure you have at least 10GB of free disk space, a 64-bit version of Windows or Linux, NVIDIA driver version 470.82.01 or later, and CUDA 11.4 or later installed.

Expected performance

You can expect ~102 tok/sec performance with 4.9GB VRAM in use, leaving 7.1GB for context. This setup allows for a practical context window of up to 32768 tokens, making it highly efficient for local development.

1. Install runtimeOllama

pip install ollama
ollama init

2. Download the model

Download the Qwen 2.5 Coder 7B Q4_K_M quantized model (4.4GB file) from Hugging Face.

ollama pull Qwen/Qwen2.5-Coder-7B-Instruct-GGUF:qwen2.5-coder-7b-instruct-q4_k_m.gguf

3. Run it

ollama run Qwen/Qwen2.5-Coder-7B-Instruct-GGUF:qwen2.5-coder-7b-instruct-q4_k_m.gguf --n-gpu-layers 32 --flash-attn
ollama chat

4. Optimize for RTX 3080 Ti

For optimal performance on the NVIDIA GeForce RTX 3080 Ti with 12GB VRAM, set --n-gpu-layers to 32 to utilize the GPU effectively. Enable --flash-attn for faster inference. With 4.9GB VRAM used by the model, you have 7.1GB of VRAM left for context, allowing for a practical context window of up to 32768 tokens.

Troubleshooting

Out of memory error during inference

Reduce --n-gpu-layers to 16 or enable --cpu-offload to offload some layers to CPU.

Slow inference speed

Ensure --flash-attn is enabled and check if your CUDA installation is up-to-date.

Model not found

Verify the model path and ensure the model is correctly downloaded and accessible.

Alternative runtimes

Alternative runtimes include LM Studio, llama.cpp, and Jan. Use LM Studio for a more user-friendly interface, llama.cpp for lightweight deployment, and Jan for advanced customization options. However, Ollama provides a balanced approach with good performance and ease of use, especially suitable for the NVIDIA GeForce RTX 3080 Ti.

Full Qwen 2.5 Coder 7B details →

Other models that run great on RTX 3080 Ti

FAQ (20)

What GPU do I need to run Qwen 2.5 Coder 7B?

To run Qwen 2.5 Coder 7B, you need a GPU with at least 4.9 GB of VRAM, but 8.0 GB is recommended for better performance, especially with higher quantization levels.

Is Qwen 2.5 Coder 7B good for coding?

Yes, Qwen 2.5 Coder 7B is specifically designed for coding tasks and performs well in generating and understanding code, making it an excellent choice for local development.

Qwen 2.5 Coder 7B vs Llama 3.1 8B?

Qwen 2.5 Coder 7B has 7.6 billion parameters and is optimized for coding, while Llama 3.1 8B has more parameters and is more general-purpose. Qwen 2.5 Coder 7B may outperform Llama 3.1 8B in specialized coding tasks.

Can I run Qwen 2.5 Coder 7B on a Mac?

Yes, you can run Qwen 2.5 Coder 7B on a Mac, provided your Mac has a compatible GPU with sufficient VRAM (at least 4.9 GB).

How much VRAM does Qwen 2.5 Coder 7B need?

Qwen 2.5 Coder 7B requires between 4.9 GB and 8.0 GB of VRAM, depending on the quantization level used.

Is Qwen 2.5 Coder 7B censored?

Qwen 2.5 Coder 7B is not censored; however, it adheres to ethical guidelines and community standards to ensure responsible use.

Is Qwen 2.5 Coder 7B commercial-use allowed?

Yes, Qwen 2.5 Coder 7B is licensed under the Apache-2.0 license, which allows for both commercial and non-commercial use.

Qwen 2.5 Coder 7B context length?

Qwen 2.5 Coder 7B supports a context length of up to 32,768 tokens, allowing for handling large codebases and complex programming tasks.

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