Kokoro 82M TTS is a compact text-to-speech model designed to convert written text into natural-sounding speech. With just 82 million parameters, this model is remarkably lightweight yet delivers surprisingly high-quality audio outputs, making it an excellent choice for applications where resource constraints are a concern. The model is built on the Kokoro architecture and is licensed under the Apache 2.0 license, ensuring it is freely available for both personal and commercial projects. Despite its small size, Kokoro 82M TTS punches well above its weight in terms of performance, offering clear and intelligible speech that can be fine-tuned for various accents and intonations.
In comparison to other models in its size class, Kokoro 82M TTS stands out for its efficiency and low memory footprint. It requires only 0.6 GB of VRAM, which means it can run smoothly on a wide range of devices, from low-end laptops to more powerful desktops. This makes it an ideal choice for developers and hobbyists who need a reliable TTS solution without the need for high-end hardware. The availability of ONNX-Q8F16 quantization further enhances its efficiency, reducing computational requirements while maintaining acceptable audio quality. Users looking for a balance between performance and resource usage, particularly in embedded systems or edge devices, will find Kokoro 82M TTS to be a valuable asset.
| Quantization | Bits | File Size | VRAM Needed | RAM Needed | Quality |
|---|---|---|---|---|---|
| ONNX-Q8F16 | 8 | 0.08 GB | 0.58 GB | 1.08 GB | 95% |
How to run Kokoro 82M TTS
Pick a runtime — copy & paste. Commands are pre-filled with this model’s repo.
GUI. Browse → download → chat. MLX on Apple Silicon.
LM Studio home →- 1
Open LM Studio
Go to the 🔍 Search tab.
- 2
Search for
onnx-community/Kokoro-82M-v1.0-ONNX - 3
Download
Pick the ONNX-Q8F16 quant — best balance of size vs. quality.
- 4
Chat
Hit ▶ Load Model and start chatting. Toggle 'Local Server' to expose an OpenAI-compatible API on :1234.
Community benchmarks
Real tokens/sec reports from people running Kokoro 82M TTS on actual hardware.
No community runs yet for this model. Be the first to submit your numbers.
how much VRAM do I need to run Kokoro 82M TTS?
Kokoro 82M TTS requires 0.58 GB VRAM minimum with ONNX-Q8F16 quantization. For full precision you need 0.58 GB.
which quant should I pick?
Q4_K_M is the best quality/VRAM balance — ~92% of FP16 quality at ~25% the footprint. Q8_0 is near-lossless if you have the headroom.
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.
Does Kokoro 82M TTS support function calling?
Kokoro 82M TTS is a text-to-speech model and does not support function calling or other advanced language model features.
Kokoro 82M TTS quantization options?
Kokoro 82M TTS supports quantization, which can reduce the model size and VRAM usage, but specific quantization options are not detailed in the documentation.
Can Kokoro 82M TTS run on CPU?
Yes, Kokoro 82M TTS can run on a CPU, but it will be slower compared to running on a GPU with 0.6 GB of VRAM.
Kokoro 82M TTS fine-tuning?
Kokoro 82M TTS can be fine-tuned to improve performance on specific datasets or voices, but this requires additional training data and computational resources.
Kokoro 82M TTS system requirements?
To run Kokoro 82M TTS, you need a system with at least 0.6 GB of VRAM, 86 MB of storage, and a compatible GPU or CPU.
Kokoro 82M TTS performance benchmark?
Performance benchmarks for Kokoro 82M TTS are not publicly available, but it is known to generate high-quality speech synthesis efficiently.
Kokoro 82M TTS for RAG?
Kokoro 82M TTS is not designed for Retrieval-Augmented Generation (RAG) but can be used in conjunction with other models to enhance speech synthesis in RAG systems.
Kokoro 82M TTS for agents?
Kokoro 82M TTS can be integrated into virtual agents to provide natural-sounding speech, enhancing user interaction and engagement.
Kokoro 82M TTS for coding vs general?
Kokoro 82M TTS is better suited for general text-to-speech tasks rather than coding-specific applications, though it can still be useful for generating spoken code snippets.
Kokoro 82M TTS vs ChatGPT?
Kokoro 82M TTS is a specialized text-to-speech model, while ChatGPT is a large language model designed for conversational AI and a wide range of text generation tasks.
Kokoro 82M TTS download size?
The download size for Kokoro 82M TTS is 86 MB.
Best quant for Kokoro 82M TTS?
The best quantization option for Kokoro 82M TTS depends on your specific needs, but it typically involves a trade-off between model size and performance. Common options include INT8 and FP16.