Can RTX 4080 SUPER run Qwen 2.5 Coder 7B?
Yes — runs locally
~78 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 4080 SUPER (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 4080 SUPER
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Qwen 2.5 Coder 7B on your NVIDIA GeForce RTX 4080 SUPER with Grade S performance, using the Q8_0 quantization for ~82 tok/sec.
Prerequisites
Before starting, ensure you have at least 10GB of free disk space, a 64-bit version of Windows or Linux, the latest NVIDIA driver (version 525.60.12 or later), and CUDA 11.8 installed.
Expected performance
With the Q8_0 quantization, you can expect ~82 tok/sec performance, with 8.0GB of VRAM used by the model. Given the remaining 8.0GB of VRAM, you can achieve a practical context window of around 16,000 tokens, which is suitable for most coding tasks.
1. Install runtimeOllama
pip install ollama
ollama config set runtime cuda2. Download the model
Download the Q8_0 quantized version of Qwen 2.5 Coder 7B (7.5GB file) from Hugging Face.
ollama pull Qwen/Qwen2.5-Coder-7B-Instruct-GGUF:qwen2.5-coder-7b-instruct-q8_0.gguf3. Run it
ollama run Qwen/Qwen2.5-Coder-7B-Instruct-GGUF:qwen2.5-coder-7b-instruct-q8_0.gguf --interactive
ollama chat --model Qwen/Qwen2.5-Coder-7B-Instruct-GGUF:qwen2.5-coder-7b-instruct-q8_0.gguf4. Optimize for RTX 4080 SUPER
For optimal performance on the NVIDIA GeForce RTX 4080 SUPER with 16GB VRAM, use the --n-gpu-layers parameter to offload layers to the GPU. Set --n-gpu-layers to 32 to balance performance and memory usage. Enable flash attention (--flash-attn) to speed up inference. With 8.0GB VRAM used by the model, you have 8.0GB of headroom for context, allowing for a practical context window of around 16,000 tokens.
Troubleshooting
Out of memory error during inference
Reduce the number of GPU layers with --n-gpu-layers 16 or lower.
Slow token generation
Ensure flash attention is enabled with --flash-attn.
Model not found
Verify the model path and ensure it is correctly downloaded and accessible.
Alternative runtimes
Alternative runtimes include LM Studio, llama.cpp, and Jan. LM Studio is a good choice for a more user-friendly interface, while llama.cpp offers fine-grained control over model parameters. Jan is suitable for lightweight deployments. For the NVIDIA GeForce RTX 4080 SUPER, Ollama provides the best balance of ease of use and performance.
Other models that run great on RTX 4080 SUPER
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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