Can RTX 5060 Ti run Qwen 2.5 Coder 14B?

Yes — runs locally

~48 tok/sec · Fast — smooth conversation. Responses feel real-time.

Your VRAM

16 GB

Model size

14B

Best quant

Q4_K_M

VRAM needed

8.9 GB

The verdict

The RTX 5060 Ti (16 GB VRAM) handles Qwen 2.5 Coder 14B comfortably using the Q4_K_M quantization, which fits in 8.9 GB. Expected throughput is around 48 tokens/second, which feels Fast — smooth conversation. Responses feel real-time. in interactive use. Powerful 14B code model. Excellent for complex programming tasks.

Setup tutorial: Qwen 2.5 Coder 14B on RTX 5060 Ti

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

TL;DR

Run Qwen 2.5 Coder 14B on an NVIDIA GeForce RTX 5060 Ti with Grade S performance at ~64 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, the latest NVIDIA drivers (version 525.60.13 or later), and CUDA 11.8 installed.

Expected performance

You can expect the model to run at ~64 tok/sec with 8.9GB of VRAM in use, leaving 7.1GB of VRAM for context. This should allow for a practical context window of around 20,000 tokens, suitable for complex programming tasks.

1. Install runtimeOllama

pip install ollama
ollama config set cuda_path /usr/local/cuda

2. Download the model

Download the Qwen 2.5 Coder 14B Q4_K_M quantized model (8.4GB file) from Hugging Face.

ollama pull bartowski/Qwen2.5-Coder-14B-Instruct-GGUF:Qwen2.5-Coder-14B-Instruct-Q4_K_M.gguf

3. Run it

ollama run Qwen2.5-Coder-14B-Instruct-Q4_K_M --n-gpu-layers 40 --flash-attn
ollama chat Qwen2.5-Coder-14B-Instruct-Q4_K_M

4. Optimize for RTX 5060 Ti

For optimal performance on the NVIDIA GeForce RTX 5060 Ti with 16GB VRAM, use --n-gpu-layers 40 to allocate most layers to the GPU while keeping some on the CPU. Enable flash attention (--flash-attn) to speed up inference and reduce VRAM usage. With 8.9GB VRAM used by the model, you will have approximately 7.1GB of VRAM left for context, allowing for a practical context window of around 20,000 tokens.

Troubleshooting

Out of memory error during inference

Reduce --n-gpu-layers to 30 or lower to free up more VRAM.

Slow inference speed

Ensure flash attention is enabled with --flash-attn and check that CUDA is properly configured.

Model fails to load

Verify that the model file is correctly downloaded and not corrupted. Try re-downloading the model.

Alternative runtimes

Alternative runtimes like LM Studio, llama.cpp, and Jan can be used for different scenarios. LM Studio offers a graphical interface and is ideal for users who prefer a GUI. llama.cpp is highly optimized for low-memory systems but may require more manual configuration. Jan is a lightweight runtime that can be useful for quick prototyping or testing, but it may not offer the same level of performance as Ollama.

Full Qwen 2.5 Coder 14B details →

Other models that run great on RTX 5060 Ti

FAQ (20)

What GPU do I need to run Qwen 2.5 Coder 14B?

To run Qwen 2.5 Coder 14B, you need a GPU with at least 8.9 GB of VRAM, but 15.1 GB is recommended for optimal performance.

Is Qwen 2.5 Coder 14B good for coding?

Yes, Qwen 2.5 Coder 14B is excellent for complex programming tasks due to its large context length of 32,768 tokens and 14 billion parameters.

Qwen 2.5 Coder 14B vs Llama 3.1 8B?

Qwen 2.5 Coder 14B has more parameters (14B vs 8B) and a longer context length (32,768 vs typically shorter), making it better suited for complex coding tasks.

Can I run Qwen 2.5 Coder 14B on a Mac?

Yes, you can run Qwen 2.5 Coder 14B on a Mac, provided your Mac has a compatible GPU with sufficient VRAM (8.9 GB minimum, 15.1 GB recommended).

How much VRAM does Qwen 2.5 Coder 14B need?

Qwen 2.5 Coder 14B requires 8.9 GB to 15.1 GB of VRAM, depending on the quantization level used.

Is Qwen 2.5 Coder 14B censored?

Qwen 2.5 Coder 14B is not inherently censored, but it adheres to community guidelines and ethical standards in its responses.

Is Qwen 2.5 Coder 14B commercial-use allowed?

Yes, Qwen 2.5 Coder 14B is licensed under Apache-2.0, which allows for commercial use.

Qwen 2.5 Coder 14B context length?

Qwen 2.5 Coder 14B has a context length of 32,768 tokens, allowing it to handle very long sequences of text.

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