Can RTX 5080 run Qwen 2.5 Coder 7B?

Yes — runs locally

~78 tok/sec · Instant — feels like typing. No noticeable delay.

Your VRAM

16 GB

Model size

7.6B

Best quant

Q8_0

VRAM needed

8.0 GB

The verdict

The RTX 5080 (16 GB VRAM) handles Qwen 2.5 Coder 7B comfortably using the Q8_0 quantization, which fits in 8.0 GB. Expected throughput is around 78 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Strong 7B code model rivaling larger coding models. Excellent for local development.

Setup tutorial: Qwen 2.5 Coder 7B on RTX 5080

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

TL;DR

Run Qwen 2.5 Coder 7B on an NVIDIA GeForce RTX 5080 with Q8_0 quantization for Grade S performance at ~82 tok/sec.

Prerequisites

Before starting, ensure you have at least 10GB of free disk space, a 64-bit version of Windows or Linux, NVIDIA driver version 510.47.03 or later, and CUDA 11.7 or later installed.

Expected performance

With the Q8_0 quantization, you can expect the model to run at approximately 82 tokens per second, using around 8.0GB of VRAM. Given the 16GB VRAM on the RTX 5080, you will have about 8.0GB of headroom for context, allowing for a practical context window of up to 32768 tokens.

1. Install runtimeOllama

pip install ollama
ollama init

2. Download the model

Download the Qwen 2.5 Coder 7B Q8_0 quantized model (7.5GB file) from Hugging Face.

ollama pull Qwen/Qwen2.5-Coder-7B-Instruct-GGUF:qwen2.5-coder-7b-instruct-q8_0.gguf

3. Run it

ollama run Qwen/Qwen2.5-Coder-7B-Instruct-GGUF:qwen2.5-coder-7b-instruct-q8_0.gguf --n-gpu-layers 32 --flash-attn --tensor-parallelism 2

4. Optimize for RTX 5080

For optimal performance on the NVIDIA GeForce RTX 5080 with 16GB VRAM, set --n-gpu-layers to 32 to utilize most of the GPU memory. Enable --flash-attn for faster attention computations and set --tensor-parallelism to 2 to distribute the workload across multiple cores. This configuration ensures that the model runs efficiently within the 16GB VRAM limit.

Troubleshooting

Out of memory error during inference

Reduce --n-gpu-layers to 24 or lower and decrease --tensor-parallelism to 1.

Slow inference speed

Ensure --flash-attn is enabled and update your NVIDIA drivers to the latest version.

Model fails to load

Verify the integrity of the downloaded model file and try re-downloading it.

Alternative runtimes

For users preferring different runtimes, consider LM Studio for a more user-friendly GUI, llama.cpp for fine-grained control over optimizations, or Jan for lightweight deployment. Ollama is recommended for its ease of use and efficient performance on the RTX 5080.

Full Qwen 2.5 Coder 7B details →

Other models that run great on RTX 5080

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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