Kokoro v0.19

Our Take

A solid 0.082B-parameter dense audio model from hexgrad. Treat the modality benchmarks above as the leading indicator of fit — composite scoring across modalities is still maturing.

Generated from this model’s benchmarks and ranking signals. Editor reviews refine it over time.

Kokoro v0.19 excels in environments where low latency is the primary requirement. Because the model is small enough to fit entirely in the L3 cache of some high-end CPUs or the dedicated VRAM of entry-level GPUs, it is ideal for:

• Real-Time Voice Assistants: The sub-100ms "time to first audio" makes it suitable for interactive agents where cloud latency would break the user experience.
• Local Screen Readers: Its lightweight nature allows it to run in the background of an OS without impacting the performance of other applications.
• Game Development: Developers can use Kokoro to generate dynamic NPC dialogue locally on the player's machine, saving on storage space compared to pre-recorded .wav files.
• Automated Content Creation: Processing large volumes of text into audio for podcasts or narrated articles at a fraction of the cost of ElevenLabs or OpenAI TTS.

In this v0.19 release, the model supports 10 distinct voices. While it lacks the advanced "emotional steering" found in massive models, the output is notably less "grainy" than older models like Coqui TTS or Espeak-NG.

Running Kokoro v0.19 locally is trivial compared to LLMs. The hardware requirements are among the lowest in the current AI ecosystem, making it accessible for almost any practitioner.

To run Kokoro v0.19, you do not need a flagship GPU. The model weights in FP16 take up less than 200MB of space.

• Minimum VRAM: 2GB (any modern integrated GPU or entry-level discrete card).
• Recommended Hardware: Apple Silicon (M1/M2/M3/M4) or NVIDIA RTX 3060 and above. On an RTX 4090, the model can generate audio so quickly that the bottleneck is often the disk I/O for saving the resulting audio file.
• CPU Inference: Unlike many LLMs, Kokoro v0.19 performs exceptionally well on standard CPUs. On an M-series Mac, it achieves real-time generation easily using the kokoro pip package.

While quantization (such as Q4_K_M or Q8_0) is the standard for LLMs, it is often unnecessary for Kokoro v0.19. Because the model is only 82M parameters, the memory savings from 4-bit quantization are negligible (reducing a ~170MB file to ~50MB), while the potential for "robotic" artifacts in the audio increases. It is recommended to run this model in FP16 or BF16 to maintain the highest vocal fidelity.

The most efficient way to get started is via the official kokoro library. It requires espeak-ng as a dependency for G2P (Grapheme-to-Phoneme) conversion. For those who prefer a containerized or managed environment, Kokoro is increasingly supported in local inference engines like Ollama, though the standalone Python implementation remains the gold standard for low-latency integration.

When evaluating Kokoro v0.19, it is best compared against other small-scale TTS models rather than 7B+ parameter multi-modal models.

• Kokoro v0.19 vs. Piper: Piper is another popular local TTS engine. While Piper is even faster and can run on a Raspberry Pi 4, Kokoro v0.19 generally offers higher prosody quality and a more "modern" sound profile. Piper can sound "flat" in comparison, whereas Kokoro's StyleTTS 2 backbone provides better inflection.
• Kokoro v0.19 vs. Bark (Small): Suno’s Bark is a GPT-style generative audio model. While Bark can produce non-verbal sounds (laughter, sighs), it is significantly heavier, slower, and prone to hallucinations. Kokoro is far more stable for long-form reading and requires a fraction of the VRAM.
• Kokoro v0.19 vs. v1.0: The v0.19 release is the "legacy" version of the current v1.0. While v1.0 expands the voice library to 54 voices and 8 languages, v0.19 remains a favorite for developers who want a battle-tested, English-centric model with a proven track record of stability in production environments.

For practitioners looking to move away from $15/month TTS subscriptions, Kokoro v0.19 is the most logical entry point for local, high-fidelity speech synthesis. Its balance of 0.082B parameters and high-quality English output makes it the current benchmark for edge-deployed TTS.