Can M4 Pro run Distil-Whisper Large v3?
Yes — runs locally
~90 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The M4 Pro (48 GB VRAM) handles Distil-Whisper Large v3 comfortably using the Q8_0 quantization, which fits in 1.9 GB. Expected throughput is around 90 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Distilled Whisper. 6x faster than large-v3 with 1% accuracy loss.
Setup tutorial: Distil-Whisper Large v3 on M4 Pro
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Distil-Whisper Large v3 on an Apple M4 Pro with Ollama using Q8_0 quantization. Expect Grade S performance at ~639 tok/sec.
Prerequisites
Before starting, ensure you have at least 2GB 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 639 tokens per second, utilizing 1.9GB of VRAM. Given the 46.1GB of remaining VRAM, you can handle large context windows, making it suitable for extensive speech processing tasks.
1. Install runtimeOllama (preferred on Apple Silicon)
brew install ollama
ollama init2. Download the model
Download the Q8_0 quantized version of Distil-Whisper Large v3 (1.4GB file) from HuggingFace.
ollama pull distil-whisper/distil-large-v3-ggml:Q8_03. Run it
ollama run distil-whisper/distil-large-v3-ggml:Q8_0
ollama chat --model distil-whisper/distil-large-v3-ggml:Q8_04. Optimize for M4 Pro
For optimal performance on the Apple M4 Pro, utilize the Metal/MLX backend to leverage the GPU's 48GB VRAM. Ensure that MPS layers are enabled to take full advantage of the unified memory architecture. With 1.9GB VRAM used by the model, you will have 46.1GB of VRAM headroom for context and other tasks.
Troubleshooting
Model fails to load due to insufficient VRAM.
Ensure you have at least 48GB of VRAM available. If not, close other applications to free up memory.
Performance is below expected 639 tok/sec.
Check if the Metal/MLX backend is enabled. Run `ollama config set backend metal` to ensure optimal performance.
Model runs but output is incorrect or delayed.
Verify that the correct quantization (Q8_0) is being used. Re-run the `ollama pull` command to ensure the model is downloaded correctly.
Alternative runtimes
Alternative runtimes include LM Studio, llama.cpp, and MLX. Use LM Studio for a more user-friendly interface, llama.cpp for more control over the command line, and MLX for advanced customization. However, Ollama is generally recommended for its ease of use and performance on Apple Silicon.
Other models that run great on M4 Pro
FAQ (20)
What GPU do I need to run Distil-Whisper Large v3?
To run Distil-Whisper Large v3, you need a GPU with at least 1.9 GB of VRAM. NVIDIA GPUs such as the GTX 1060 or higher are recommended.
Is Distil-Whisper Large v3 good for coding?
Distil-Whisper Large v3 is primarily designed for speech recognition tasks and may not be optimized for coding-specific tasks. For coding, models like Codex or CodeLlama are more suitable.
Distil-Whisper Large v3 vs Llama 3.1 8B?
Distil-Whisper Large v3 has 0.76B parameters and is optimized for speech recognition, while Llama 3.1 8B is a larger, more versatile model with 8B parameters, better suited for a wider range of NLP tasks.
Can I run Distil-Whisper Large v3 on a Mac?
Yes, you can run Distil-Whisper Large v3 on a Mac, but ensure your Mac has a compatible GPU with at least 1.9 GB of VRAM. M1 and later Macs with Metal support are recommended.
How much VRAM does Distil-Whisper Large v3 need?
Distil-Whisper Large v3 requires 1.9 GB of VRAM, which is consistent across different quantization levels.
Is Distil-Whisper Large v3 censored?
No, Distil-Whisper Large v3 is not censored. It is an open-source model under the MIT license, allowing for unrestricted use and modification.
Is Distil-Whisper Large v3 commercial-use allowed?
Yes, Distil-Whisper Large v3 is licensed under the MIT license, which allows for commercial use without restrictions.
Distil-Whisper Large v3 context length?
The context length for Distil-Whisper Large v3 is currently unknown. For more detailed information, refer to the model's documentation or source code.
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