Can RTX 4060 Ti 16GB run Qwen 2.5 14B?

Yes — runs locally

~0 tok/sec · Cannot run — model too large for this GPU

Your VRAM

16 GB

Model size

14B

Best quant

Q4_K_M

VRAM needed

8.9 GB

The verdict

The RTX 4060 Ti 16GB (16 GB VRAM) handles Qwen 2.5 14B comfortably using the Q4_K_M quantization, which fits in 8.9 GB. Expected throughput is around 0 tokens/second, which feels Cannot run — model too large for this GPU in interactive use. Strong 14B model with excellent coding and reasoning. iPad Pro recommended.

Setup tutorial: Qwen 2.5 14B on RTX 4060 Ti 16GB

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

TL;DR

Qwen 2.5 14B runs with Grade S performance on an NVIDIA GeForce RTX 4060 Ti 16GB, using the Q4_K_M quantization. Expect ~64 tokens/second with snappy responsiveness.

Prerequisites

Before starting, ensure you have at least 10GB of free disk space, a compatible operating system (Windows 10/11 or Linux), the latest NVIDIA drivers (version 525.60.13 or later), and CUDA 11.8 installed.

Expected performance

With the Q4_K_M quantization, you should expect ~64 tokens/second, with 8.9GB VRAM in use, leaving 7.1GB for context. This allows for a practical context window of around 131072 tokens, ensuring smooth and responsive interactions.

1. Install runtimeOllama

pip install ollama
ollama init

2. Download the model

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

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

3. Run it

ollama run Qwen2.5-14B-Instruct-Q4_K_M --n-gpu-layers 14 --flash-attn --tensor-parallelism 1

4. Optimize for RTX 4060 Ti 16GB

For optimal performance on the NVIDIA GeForce RTX 4060 Ti 16GB, set --n-gpu-layers to 14 to utilize the 16GB VRAM effectively. Enable --flash-attn to speed up attention computations. Given the 16GB VRAM, you can achieve a practical context window of around 131072 tokens with 8.9GB VRAM in use and 7.1GB headroom.

Troubleshooting

Out of memory error during inference

Reduce the number of --n-gpu-layers or decrease the context length to fit within the 16GB VRAM limit.

Slow token generation

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

Model fails to load

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

Alternative runtimes

Alternative runtimes include LM Studio and llama.cpp. LM Studio offers a more user-friendly interface and is suitable for users who prefer a graphical environment. llama.cpp provides more control over low-level optimizations and is ideal for advanced users. For the NVIDIA GeForce RTX 4060 Ti 16GB, Ollama is recommended for its ease of use and performance.

Full Qwen 2.5 14B details →

Other models that run great on RTX 4060 Ti 16GB

FAQ (20)

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

To run Qwen 2.5 14B, you need a GPU with at least 8.9 GB of VRAM, but 15.1 GB is recommended for optimal performance, especially for larger context lengths and higher precision.

Is Qwen 2.5 14B good for coding?

Yes, Qwen 2.5 14B is excellent for coding tasks, offering strong performance in generating code, understanding complex programming concepts, and providing detailed explanations.

Qwen 2.5 14B vs Llama 3.1 8B?

Qwen 2.5 14B has more parameters (14B vs 8B), which generally results in better performance in complex tasks like coding and reasoning, but requires more VRAM and computational resources.

Can I run Qwen 2.5 14B on a Mac?

Yes, you can run Qwen 2.5 14B on a Mac, but ensure your Mac has a compatible GPU with sufficient VRAM. M1/M2 chips with Metal support can also run the model efficiently.

How much VRAM does Qwen 2.5 14B need?

Qwen 2.5 14B requires between 8.9 GB and 15.1 GB of VRAM, depending on the quantization level used. Higher quantization levels reduce VRAM usage but may slightly impact performance.

Is Qwen 2.5 14B censored?

Qwen 2.5 14B is not inherently censored, but it adheres to ethical guidelines and content policies to ensure responsible use and avoid harmful or inappropriate content.

Is Qwen 2.5 14B commercial-use allowed?

Yes, Qwen 2.5 14B is licensed under the Apache-2.0 license, which allows commercial use as long as you comply with the terms of the license.

Qwen 2.5 14B context length?

Qwen 2.5 14B supports a context length of up to 131,072 tokens, making it suitable for handling very long documents and conversations.

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