Can M4 Max run Whisper Large v3 Turbo?
Yes — runs locally
~102 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The M4 Max (128 GB VRAM) handles Whisper Large v3 Turbo comfortably using the Q8_0 quantization, which fits in 2.0 GB. Expected throughput is around 102 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Optimized large Whisper model. Near-best accuracy with faster inference.
Setup tutorial: Whisper Large v3 Turbo on M4 Max
AI-generated, GPU-specific. Verified commands for your exact hardware.
Whisper Large v3 Turbo runs at Grade S on the Apple M4 Max with Q8_0 quantization, achieving ~1629 tok/sec.
Prerequisites
Before starting, ensure you have at least 1.5GB 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
With the Q8_0 quantization, you can expect the model to run at approximately 1629 tokens per second, using around 2.0GB of VRAM. Given the 128GB VRAM, you will have 126.0GB of headroom, which should allow for processing very long audio files 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 version of Whisper Large v3 Turbo (1.5GB file) from Hugging Face.
ollama pull ggerganov/whisper.cpp:ggml-large-v3-turbo.bin3. Run it
ollama run ggerganov/whisper.cpp:ggml-large-v3-turbo.bin --input-path /path/to/audio/file.mp3 --output-path /path/to/output/transcription.txt4. Optimize for M4 Max
To optimize performance on the Apple M4 Max, ensure that you are using the Metal/MLX backend to leverage the GPU and unified memory. The 128GB VRAM allows for significant headroom, enabling efficient handling of large context lengths and batch sizes. Set the environment variable `MPS_VISIBLE_DEVICES=0` to utilize the MPS layers effectively.
Troubleshooting
The model runs slowly or crashes.
Ensure that the Metal/MLX backend is enabled and that the MPS layers are properly configured. Run `export MPS_VISIBLE_DEVICES=0` before starting the model.
The transcription output is incomplete or incorrect.
Check the input audio file for any issues such as incorrect format or corruption. Ensure the file path is correct and accessible.
The model fails to load.
Verify that the model file has been downloaded correctly and is not corrupted. Try re-downloading the model using the `ollama pull` command.
Alternative runtimes
While Ollama is the preferred runtime for Apple Silicon, you can also use LM Studio for a more graphical interface, llama.cpp for more customization options, or MLX for direct Metal integration. Jan is another lightweight option but may not offer the same performance optimizations as Ollama on the Apple M4 Max.
Other models that run great on M4 Max
FAQ (20)
What GPU do I need to run Whisper Large v3 Turbo?
To run Whisper Large v3 Turbo, you need a GPU with at least 2.0 GB of VRAM. The exact VRAM requirement can vary slightly depending on the quantization level used.
Is Whisper Large v3 Turbo good for coding?
Whisper Large v3 Turbo is primarily designed for speech recognition tasks and may not be optimized for coding-related tasks. For coding, models like Codex or CodeLLaMa might be more suitable.
Whisper Large v3 Turbo vs Llama 3.1 8B?
Whisper Large v3 Turbo has 0.81 billion parameters and is optimized for speech recognition, while Llama 3.1 8B has 8 billion parameters and is more versatile for general language tasks. Choose based on your specific needs.
Can I run Whisper Large v3 Turbo on a Mac?
Yes, you can run Whisper Large v3 Turbo on a Mac as long as your Mac has a compatible GPU with at least 2.0 GB of VRAM. Ensure you have the necessary drivers and libraries installed.
How much VRAM does Whisper Large v3 Turbo need?
Whisper Large v3 Turbo requires at least 2.0 GB of VRAM. The exact amount can vary slightly depending on the quantization level used.
Is Whisper Large v3 Turbo censored?
Whisper Large v3 Turbo is not censored. It is an open-source model released under the MIT license, allowing for broad usage without content restrictions.
Is Whisper Large v3 Turbo commercial-use allowed?
Yes, Whisper Large v3 Turbo is licensed under the MIT license, which allows for commercial use without additional restrictions.
Whisper Large v3 Turbo context length?
The context length for Whisper Large v3 Turbo is currently unknown. Refer to the official documentation or model repository for the most accurate information.
Want personalized recommendations for your exact setup? Detect my hardware →