GraySoft
Projects Models Compare Cloud benchmarks FAQ Download guIDE →
Model Intelligence Sheet

cstr/parakeet-ctc-0.6b-GGUF overview

Parakeet CTC 0.6B — GGUF ggml quantised GGUF / ggml conversions of nvidia/parakeet ctc 0.6b https://huggingface.co/nvidia/parakeet ctc 0.6b for use with the cr…

ggmlggufaudiospeech-recognitiontranscriptionparakeetctcfastconformerautomatic-speech-recognitionenbase_model:nvidia/parakeet-ctc-0.6bbase_model:quantized:nvidia/parakeet-ctc-0.6blicense:cc-by-4.0region:us

Runs locally from ~366.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
586
Likes
0
Pipeline
automatic-speech-recognition
Author

Repository Files & Downloads

4 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
parakeet-ctc-0.6b-q4_k.ggufGGUFQ4_K366.0 MBDownload
parakeet-ctc-0.6b-q5_0.ggufGGUFQ5_0429.4 MBDownload
parakeet-ctc-0.6b-q8_0.ggufGGUFQ8_0619.8 MBDownload
parakeet-ctc-0.6b.ggufGGUFGGUF1.14 GBDownload

Model Details

Model IDcstr/parakeet-ctc-0.6b-GGUF
Authorcstr
Pipelineautomatic-speech-recognition
Licensecc-by-4.0
Base modelnvidia/parakeet-ctc-0.6b
Last modified2026-08-02T15:35:02.000Z

Model README

---

license: cc-by-4.0

language:

  • en

pipeline_tag: automatic-speech-recognition

tags:

  • audio
  • speech-recognition
  • transcription
  • ggml
  • gguf
  • parakeet
  • ctc
  • fastconformer

library_name: ggml

base_model: nvidia/parakeet-ctc-0.6b

---

Parakeet CTC 0.6B — GGUF (ggml-quantised)

GGUF / ggml conversions of nvidia/parakeet-ctc-0.6b for use with the crispasr CLI from CrispStrobe/CrispASR.

Parakeet CTC 0.6B is NVIDIA's 600 M-parameter English ASR model:

  • English-only, lowercase output (matches the upstream training convention)
  • FastConformer encoder (24 layers, d_model=1024, 8 heads) + single CTC head — single forward pass per utterance, no autoregressive joint loop
  • CC-BY-4.0 licence
  • Strong WERs on the standard suite: LibriSpeech-clean 1.87 %, LibriSpeech-other 3.76 %, TEDLIUM-v3 3.78 %, GigaSpeech 10.35 %, Common Voice 7.00 %

This repo provides four quantisations, all converted from the upstream .nemo checkpoint via models/convert-stt-fastconformer-ctc-to-gguf.py (the same converter used for stt_en_fastconformer_ctc_*, since parakeet-ctc-0.6b shares the FastConformer-CTC architecture) and quantised with crispasr-quantize.

Files

| File | Size | Notes |

| --- | ---: | --- |

| parakeet-ctc-0.6b.gguf | ~1.22 GB | F16, full precision |

| parakeet-ctc-0.6b-q8_0.gguf | ~720 MB | Q8_0, near-lossless |

| parakeet-ctc-0.6b-q5_0.gguf | ~520 MB | Q5_0 |

| parakeet-ctc-0.6b-q4_k.gguf | ~455 MB | Q4_K — recommended default |

All quantisations produce the same JFK 11 s transcript.

Quick start

# 1. Build the runtime
git clone https://github.com/CrispStrobe/CrispASR
cd CrispASR
cmake -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build -j$(nproc) --target crispasr-cli

# 2. Run — the CLI auto-downloads Q4_K from this repo by friendly name:
./build/bin/crispasr -m parakeet-ctc-0.6b -f your-audio.wav

# Or pre-download a specific quant via huggingface_hub and point to it:
python -c "from huggingface_hub import hf_hub_download; print(hf_hub_download('cstr/parakeet-ctc-0.6b-GGUF', 'parakeet-ctc-0.6b-q8_0.gguf'))"
./build/bin/crispasr -m parakeet-ctc-0.6b-q8_0.gguf -f your-audio.wav

The crispasr CLI auto-detects the backend from filename — parakeet-ctc-.gguf routes to fastconformer-ctc because the architecture is identical to the stt_en_fastconformer_ctc_ family. Registry key parakeet-ctc-0.6b triggers Q4_K auto-download.

Model architecture

| Component | Details |

| --- | --- |

| Encoder | 24-layer FastConformer, d=1024, 8 heads, head_dim=128, FFN=4096, conv kernel=9, attention biases ON |

| Subsampling | dw_striding stack, 8× temporal (50 → 12.5 fps) |

| CTC head | Conv1d(1024 → 1025), k=1; vocab 1024 SentencePiece + 1 blank |

| Audio | 16 kHz mono, 80 mel bins, n_fft=512, hop=160, win=400 |

| Parameters | ~600 M |

The mel filterbank and Hann window are baked into the GGUF (preprocessor.fb, preprocessor.window). BatchNorm in the convolution module is folded into the depthwise conv weights at load time.

Performance (Apple M1 Metal, JFK 11 s, q8_0)

| Path | Median wallclock | RT× |

| --- | ---: | ---: |

| crispasr ctypes Session, Metal | 0.46 s | 24.1× |

| onnx-asr (CPU EP, int8) | 0.72 s | 15.2× |

| onnx-asr (CoreML EP, int8) | 1.28 s | 8.6× |

(Apples-to-apples on CTC-vs-CTC at the same param count vs istupakov/parakeet-ctc-0.6b-onnx. See PERFORMANCE.md for the full methodology.)

Output convention

The upstream model emits lowercase, un-punctuated English. If you need cased + punctuated output, pair with the parakeet-tdt-0.6b-v3 (cstr/parakeet-tdt-0.6b-v3-GGUF) instead, or post-process via crispasr's --punc-model (FireRedPunc / fullstop-punc).

Attribution

Related

License

CC-BY-4.0, inherited from the base model. Use of these GGUF files must comply with the CC-BY-4.0 license including attribution.

Provenance and EU AI Act Art. 53 note

  • Upstream model: nvidia/parakeet-ctc-0.6b — published by nvidia.
  • Upstream licence: cc-by-4.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
  • What was done here: format conversion and/or quantisation only (GGUF/GGML). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
  • Training data: documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
  • Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.

Run cstr/parakeet-ctc-0.6b-GGUF with guIDE

Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.

Download guIDE → · Browse 524k+ models · Compare models

Source: Hugging Face · Compare models