Can M4 Max run Qwen 2.5 14B?

Yes — runs locally

~36 tok/sec · Fast — smooth conversation. Responses feel real-time.

Your VRAM

128 GB

Model size

14B

Best quant

Q8_0

VRAM needed

15.1 GB

The verdict

The M4 Max (128 GB VRAM) handles Qwen 2.5 14B comfortably using the Q8_0 quantization, which fits in 15.1 GB. Expected throughput is around 36 tokens/second, which feels Fast — smooth conversation. Responses feel real-time. in interactive use. Strong 14B model with excellent coding and reasoning. iPad Pro recommended.

Setup tutorial: Qwen 2.5 14B on M4 Max

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

TL;DR

Run Qwen 2.5 14B on an Apple M4 Max with Grade S performance at ~130 tok/sec using the Q8_0 quantization. Requires 15.1GB VRAM, leaving ample headroom.

Prerequisites

Before starting, ensure you have at least 15GB of free disk space, macOS 12.3 or later, and Xcode Command Line Tools installed. You can install Xcode CLT by running `xcode-select --install` in your terminal.

Expected performance

You can expect the model to run at approximately 130 tokens per second, utilizing 15.1GB of VRAM. Given the remaining 112.9GB of VRAM, you can achieve a practical context window of up to 131072 tokens, making it highly suitable for complex tasks requiring extensive context.

1. Install runtimeOllama (preferred on Apple Silicon)

brew install ollama
ollama init

2. Download the model

Download the Qwen 2.5 14B Q8_0 quantized model (14.6GB file) from Hugging Face.

ollama pull bartowski/Qwen2.5-14B-Instruct-GGUF:Qwen2.5-14B-Instruct-Q8_0.gguf

3. Run it

ollama run Qwen2.5-14B-Instruct-Q8_0.gguf
ollama chat

4. Optimize for M4 Max

To optimize performance on the Apple M4 Max, ensure you are using the Metal/MLX backend. The 128GB VRAM provides significant headroom, allowing for efficient use of MPS layers and unified memory. With 15.1GB VRAM used by the model, you have 112.9GB available for context and other tasks.

Troubleshooting

If you encounter issues with the Metal/MLX backend, try reinstalling Ollama with the latest version.

brew uninstall ollama && brew install ollama

If the model runs slowly, ensure that you have the latest macOS updates installed.

softwareupdate --install --all

If you run out of VRAM, consider reducing the context length or using a smaller quantization.

ollama run Qwen2.5-14B-Instruct-Q8_0.gguf --context-length=65536

Alternative runtimes

While Ollama is the preferred runtime for Apple Silicon, you can also use LM Studio for a graphical interface, llama.cpp for more control over quantization, or MLX for direct Metal integration. Jan is another option for advanced users who need fine-grained control over the inference process. Choose based on your specific needs and comfort level with the command line.

Full Qwen 2.5 14B details →

Other models that run great on M4 Max

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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