Can M3 Max run Whisper Large v3?
Yes — runs locally
~102 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The M3 Max (128 GB VRAM) handles Whisper Large v3 comfortably using the Q8_0 quantization, which fits in 3.4 GB. Expected throughput is around 102 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Largest Whisper model. Best accuracy across all languages and accents.
Setup tutorial: Whisper Large v3 on M3 Max
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Whisper Large v3 on an Apple M3 Max with Ollama using the Q8_0 quantization. Expect Grade S performance at ~904 tok/sec.
Prerequisites
Before starting, ensure you have at least 3.5GB 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 ~904 tok/sec performance, utilizing 3.4GB of the 128GB VRAM. This leaves approximately 124.6GB of VRAM for context, enabling you to process longer audio clips 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 (2.9GB file) from the Hugging Face repository.
ollama pull ggerganov/whisper.cpp:ggml-large-v3.bin3. Run it
ollama run ggerganov/whisper.cpp:ggml-large-v3.bin
ollama stream ggerganov/whisper.cpp:ggml-large-v3.bin <input_audio_file>4. Optimize for M3 Max
For optimal performance on the Apple M3 Max, leverage the Metal/MLX backend to utilize the 128GB of unified memory. Ensure that MPS layers are enabled to take full advantage of the GPU. The large amount of VRAM allows for efficient handling of the 3.4GB VRAM requirement, leaving ample headroom for context and other tasks.
Troubleshooting
If you encounter an 'MPS not found' error, ensure that the Metal Performance Shaders (MPS) framework is properly installed and enabled.
Install the latest macOS updates and verify that the MPS framework is included in your system configuration.
If the model runs but the performance is significantly lower than expected, check if the Metal/MLX backend is being used.
Set the environment variable `OLLAMA_BACKEND=metal` before running the model: `export OLLAMA_BACKEND=metal`.
If you experience out-of-memory errors despite having 128GB VRAM, ensure that other applications are not consuming excessive memory.
Close unnecessary applications and processes to free up more VRAM for the model.
Alternative runtimes
While Ollama is the preferred runtime for Apple Silicon, you can also use alternatives like LM Studio, llama.cpp, or MLX. LM Studio offers a graphical interface and is useful for users who prefer a visual setup. llama.cpp is a lightweight option for command-line enthusiasts, and MLX provides additional flexibility for custom optimizations. Choose based on your specific needs and comfort level with the command line.
Other models that run great on M3 Max
FAQ (20)
What GPU do I need to run Whisper Large v3?
To run Whisper Large v3, you need a GPU with at least 3.4 GB of VRAM. NVIDIA GPUs like the RTX 2060 or higher are recommended for optimal performance.
Is Whisper Large v3 good for coding?
Whisper Large v3 is primarily designed for speech recognition and not for coding tasks. It excels in transcribing audio and handling multilingual content.
Whisper Large v3 vs Llama 3.1 8B?
Whisper Large v3 has 1.55B parameters and is optimized for speech recognition, while Llama 3.1 8B has 8B parameters and is more suited for text generation and language understanding tasks.
Can I run Whisper Large v3 on a Mac?
Yes, you can run Whisper Large v3 on a Mac, but ensure your Mac has a compatible GPU with at least 3.4 GB of VRAM for smooth operation.
How much VRAM does Whisper Large v3 need?
Whisper Large v3 requires 3.4 GB of VRAM, regardless of quantization level, to run efficiently.
Is Whisper Large v3 censored?
Whisper Large v3 is not censored. It is designed to handle a wide range of audio inputs and transcribe them accurately without restrictions.
Is Whisper Large v3 commercial-use allowed?
Yes, Whisper Large v3 is licensed under the MIT license, which allows for both commercial and non-commercial use.
Whisper Large v3 context length?
The context length for Whisper Large v3 is not explicitly defined, but it is designed to handle long audio segments effectively.
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