Can M3 Max run Kokoro 82M TTS?
Yes — runs locally
~102 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The M3 Max (128 GB VRAM) handles Kokoro 82M TTS comfortably using the ONNX-Q8F16 quantization, which fits in 0.6 GB. Expected throughput is around 102 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. High quality 82M parameter TTS model. Excellent speech synthesis with multiple voice options. 86MB download.
Setup tutorial: Kokoro 82M TTS on M3 Max
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Kokoro 82M TTS on an Apple M3 Max with Ollama using the ONNX-Q8F16 quantization. Expect Grade S performance at ~3274 tok/sec.
Prerequisites
Before starting, ensure you have at least 1GB of free disk space, macOS 12 (Monterey) or later, and Xcode Command Line Tools installed. You can install Xcode CLT with `xcode-select --install`.
Expected performance
With the ONNX-Q8F16 quantization, expect the model to run at approximately 3274 tokens per second, using around 0.6GB of VRAM. This leaves you with 127.4GB of VRAM for context, allowing for very large input sequences without running into memory constraints.
1. Install runtimeOllama (preferred on Apple Silicon)
brew install ollama
ollama init2. Download the model
Download the 86MB ONNX-Q8F16 quantized model from Hugging Face.
ollama pull onnx-community/Kokoro-82M-v1.0-ONNX:q8f163. Run it
ollama run onnx-community/Kokoro-82M-v1.0-ONNX:q8f16
ollama chat onnx-community/Kokoro-82M-v1.0-ONNX:q8f164. Optimize for M3 Max
For optimal performance on the Apple M3 Max, leverage the Metal/MLX backend to utilize the 128GB unified memory effectively. Ensure that MPS layers are enabled to take full advantage of the GPU's capabilities. With 128GB VRAM, you have ample headroom for large contexts and multiple concurrent tasks.
Troubleshooting
Low performance or high latency
Ensure that the Metal/MLX backend is properly configured and that MPS layers are enabled. You can check and enable them with `ollama config set backend metal`.
Out-of-memory errors
Reduce the batch size or context length. You can adjust these settings in the Ollama configuration with `ollama config set batch_size <value>` and `ollama config set context_length <value>`.
Model not found after pulling
Verify that the model was successfully downloaded by checking the Ollama cache directory with `ollama models`. If the model is missing, try pulling it again with `ollama pull onnx-community/Kokoro-82M-v1.0-ONNX:q8f16`.
Alternative runtimes
While Ollama is the preferred runtime for Apple Silicon, you can also consider LM Studio for a more graphical interface, llama.cpp for lightweight deployments, MLX for direct Metal integration, and Jan for advanced customization. Choose an alternative based on your specific use case and preferences.
Other models that run great on M3 Max
FAQ (20)
What GPU do I need to run Kokoro 82M TTS?
Kokoro 82M TTS requires at least 0.6 GB of VRAM. Any modern GPU with this amount of VRAM should suffice.
Is Kokoro 82M TTS good for coding?
Kokoro 82M TTS is primarily designed for text-to-speech applications and not specifically for coding. However, it can be useful for generating spoken code snippets or documentation.
Kokoro 82M TTS vs Llama 3.1 8B?
Kokoro 82M TTS is a smaller, more focused model for text-to-speech with 82 million parameters, while Llama 3.1 8B is a larger, more versatile language model with 8 billion parameters, suitable for a wider range of tasks.
Can I run Kokoro 82M TTS on a Mac?
Yes, you can run Kokoro 82M TTS on a Mac as long as your system meets the minimum VRAM requirement of 0.6 GB.
How much VRAM does Kokoro 82M TTS need?
Kokoro 82M TTS requires 0.6 GB of VRAM to run smoothly.
Is Kokoro 82M TTS censored?
Kokoro 82M TTS is not inherently censored, but its output can be controlled through the input and configuration settings.
Is Kokoro 82M TTS commercial-use allowed?
Yes, Kokoro 82M TTS is licensed under the Apache-2.0 license, which allows for commercial use.
Kokoro 82M TTS context length?
The context length for Kokoro 82M TTS is currently unknown, but it is designed to handle typical text-to-speech inputs effectively.
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