Parakeet TDT 0.6B V3: Core ML encoder and GGUF decoder
This repository contains the optional Apple Silicon package for Parakeet TDT
0.6B V3 (GGUF) in Glimpse. It requires the transcribe.cpp Parakeet Core ML
adapter with decoder-only GGUF support. The application dependency integration
is under development; these are not standalone transcription executables.
| File |
Download size |
Purpose |
parakeet-tdt-0.6b-v3-Q8_0-decoder.gguf |
19.48 MB |
Predictor, joint network, tokenizer and model metadata |
parakeet-tdt-0.6b-v3-Q8_0-encoder.mlmodelc.zip |
1.09 GB |
Compiled Core ML encoder |
The combined download is 1.11 GB, without duplicating the encoder weights
in the GGUF. For CPU/GPU transcription on Windows or Mac, use
Handy's full Q8_0 GGUF
instead. The Core ML package requires Apple Silicon.
Provenance
The model originates from NVIDIA Parakeet TDT 0.6B V3,
licensed CC BY 4.0. Both artifacts derive from Handy's
parakeet-tdt-0.6b-v3-Q8_0.gguf using transcribe.cpp's
scripts/convert-parakeet-gguf-to-coreml.py and
scripts/extract-parakeet-decoder.py. Extraction preserves predictor/joint
weights and metadata and sets stt.parakeet.decoder_only=true.
| Artifact |
SHA-256 |
| Original full GGUF |
5859f77944efcd8eafa23a6350731960b2b55b2203df51f319665c807d802cc7 |
| Decoder-only GGUF |
dfcf670a00df8d49474fddea707bcfc77339789f65dde115aeb79570fc813744 |
| Encoder ZIP |
7d90a75d6c9bad2f082782545adbea0df430703dc84f90404e1fe322552a563d |
Runtime requirements
Extract the ZIP next to the decoder GGUF, retaining the
parakeet-tdt-0.6b-v3-Q8_0-encoder.mlmodelc directory name. A native caller must
pass that directory through the Core ML session option. Glimpse-Speech detects
the companion beside the -decoder.gguf file.
The encoder accepts 128 mel bins and up to 1501 frames, using a length mask.
It uses FP16 Core ML computation with CPU and Neural Engine allowed and GPU
excluded. The predictor/joint decoder runs on CPU. Core ML may use CPU
operations; this is not a guarantee of exclusive Neural Engine execution.
Glimpse splits long recordings into chunks within the encoder capacity. Native
decoder-only calls beyond capacity return an error; there is no embedded ggml
encoder to fall back to. Full GGUF calls retain the normal CPU/GPU fallback.
The export supports offline TDT V3, not Unified or Nemotron streaming.
It does not add custom-word biasing, streaming, or speaker diarization.
FP16 output can differ from ggml; no multilingual accuracy equivalence is claimed.
Glimpse
These files power on-device dictation on Apple Silicon in Glimpse, a free, open-source dictation app for Mac and Windows. The source is on GitHub.
