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library_name: mlx
license: mit
language:
- ru
- en
tags:
- automatic-speech-recognition
- mlx
- apple-silicon
- russian
- gigaam
- conformer
- rnnt
base_model: ai-sage/GigaAM-v3
pipeline_tag: automatic-speech-recognition
---
# GigaAM v3 e2e RNNT — MLX
MLX port of [GigaAM-v3](https://github.com/salute-developers/GigaAM) RNNT variant for Apple Silicon. Higher quality than CTC, ~77x realtime on M2 Max.
## Usage
```bash
pip install git+https://github.com/aystream/gigaam-mlx.git
```
```python
from gigaam_mlx import load_model, transcribe
model, tokenizer = load_model("rnnt") # downloads automatically
text = transcribe(model, tokenizer, "recording.wav")
```
Or via CLI:
```bash
gigaam-mlx recording.wav --model-type rnnt
```
## CTC vs RNNT
| Variant | Speed (20s chunk) | Quality | Full 18-min video |
|---|---|---|---|
| [CTC](https://huggingface.co/aystream/GigaAM-v3-e2e-ctc-mlx) | 0.06s (~330x) | Good | 21.5s |
| **RNNT (this)** | **0.26s (~77x)** | **Better** | **25.0s** |
## Links
- **Code:** [github.com/aystream/gigaam-mlx](https://github.com/aystream/gigaam-mlx)
- **CTC variant:** [aystream/GigaAM-v3-e2e-ctc-mlx](https://huggingface.co/aystream/GigaAM-v3-e2e-ctc-mlx)
- **Original:** [salute-developers/GigaAM](https://github.com/salute-developers/GigaAM) ([paper](https://arxiv.org/abs/2506.01192))
- **License:** MIT
|