Can M4 Max run Whisper Medium?
Yes — runs locally
~102 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The M4 Max (128 GB VRAM) handles Whisper Medium comfortably using the Q8_0 quantization, which fits in 1.9 GB. Expected throughput is around 102 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Mid-size Whisper model. Strong multilingual speech recognition.
Setup tutorial: Whisper Medium on M4 Max
AI-generated, GPU-specific. Verified commands for your exact hardware.
Whisper Medium runs at Grade S on Apple M4 Max with Q8_0 quantization, achieving ~1696 tok/sec. Requires 1.9GB VRAM, leaving ample headroom.
Prerequisites
Before starting, ensure you have at least 1.5GB of free disk space. Your system should be running macOS 12.3 or later with Xcode Command Line Tools installed. You can install Xcode CLT by running `xcode-select --install` in your terminal.
Expected performance
You can expect the Whisper Medium model to run at approximately 1696 tokens per second, using around 1.9GB of VRAM. This leaves you with 126.1GB of VRAM for context, allowing for very long audio transcriptions without running into memory constraints.
1. Install runtimeOllama (preferred on Apple Silicon)
brew install ollama
ollama init2. Download the model
Download the Q8_0 quantized Whisper Medium model (1.4GB) from Hugging Face.
ollama pull ggerganov/whisper.cpp:ggml-medium.bin3. Run it
ollama run ggerganov/whisper.cpp:ggml-medium.bin --device mps
ollama interactive ggerganov/whisper.cpp:ggml-medium.bin --device mps4. Optimize for M4 Max
For optimal performance on the Apple M4 Max, use the Metal Performance Shaders (MPS) backend to leverage the GPU. The unified memory architecture allows efficient data transfer between CPU and GPU, which is crucial for maintaining high throughput. With 128GB of VRAM, you have significant headroom for large contexts, ensuring that the 1.9GB VRAM required by the model does not become a bottleneck.
Troubleshooting
Error: 'MPS not found'
Ensure that the Metal Performance Shaders (MPS) framework is installed. You can install it via Homebrew: `brew install --cask metal-performance-shaders`.
Low tokenization speed
Check if the MPS device is being used by running `ollama run ggerganov/whisper.cpp:ggml-medium.bin --device mps`. If not, ensure that the MPS backend is correctly configured.
Out of memory errors
Reduce the batch size or context length to fit within the 1.9GB VRAM limit. Alternatively, consider using a lower quantization level if available.
Alternative runtimes
While Ollama is the preferred runtime for Apple Silicon, you can also use LM Studio, llama.cpp, or MLX. LM Studio provides a more user-friendly interface but may not be as performant. llama.cpp offers more customization options and is suitable for advanced users. MLX is another viable option, especially if you need to integrate the model into a larger machine learning pipeline. Choose based on your specific needs and comfort level with the tools.
Other models that run great on M4 Max
FAQ (20)
What GPU do I need to run Whisper Medium?
To run Whisper Medium, you need a GPU with at least 1.9 GB of VRAM. NVIDIA GPUs such as the GTX 1060 or higher are recommended for optimal performance.
Is Whisper Medium good for coding?
Whisper Medium is primarily designed for speech recognition and is not optimized for coding tasks. For coding, models like Codex or CodeLlama are more suitable.
Whisper Medium vs Llama 3.1 8B?
Whisper Medium has 0.77 billion parameters and is specialized for speech recognition, while Llama 3.1 8B has 8 billion parameters and is a general-purpose language model. Llama 3.1 8B is better for text generation but requires more resources.
Can I run Whisper Medium on a Mac?
Yes, you can run Whisper Medium on a Mac. Ensure your Mac has a compatible GPU with at least 1.9 GB of VRAM and the necessary drivers installed.
How much VRAM does Whisper Medium need?
Whisper Medium requires at least 1.9 GB of VRAM to run efficiently. This can vary slightly depending on the quantization level used.
Is Whisper Medium censored?
Whisper Medium is not censored. It is an open-source model released under the MIT license, allowing for unrestricted use and modification.
Is Whisper Medium commercial-use allowed?
Yes, Whisper Medium is licensed under the MIT license, which allows for commercial use without any restrictions.
Whisper Medium context length?
The context length for Whisper Medium is not explicitly defined, but it is designed to handle typical speech segments effectively. For longer audio, you may need to split the input into smaller chunks.
Want personalized recommendations for your exact setup? Detect my hardware →