---
license: cc-by-4.0
library_name: coreai
pipeline_tag: automatic-speech-recognition
base_model: nvidia/parakeet-tdt-0.6b-v3
tags: [core-ai, coreaikit, parakeet, tdt, rnn-t, transducer, asr, on-device, apple]
---

# Parakeet-TDT-0.6B — Core AI

[`nvidia/parakeet-tdt-0.6b-v3`](https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3) (cc-by-4.0, 600M)
converted to **Apple Core AI** `.aimodel` — the first **transducer / TDT (RNN-T family)** ASR in the
[zoo](https://github.com/john-rocky/coreai-models-community). Transcribes ≤~29 s clips in 25
European languages as **three stateless graphs + a host greedy loop** (no LLM runtime).

- `parakeet_encoder_float16_L2885.aimodel` — FastConformer encoder + projector (fp16, ~1.2 GB),
  `mel[1,128,2885] → enc_proj[1,361,640]`.
- `parakeet_predict_float32.aimodel` — embedding → 2-layer LSTM → projector (fp32),
  `token[1,1],h,c[2,1,640] → dec_out[1,640],h',c'`.
- `parakeet_joint_float32.aimodel` — `head(relu(enc_frame+dec_out))` (fp32),
  `→ token_logits[1,8193], dur_logits[1,5]`.
- `tokenizer.json` (+ `tokenizer_config.json`), `mel_filters_128x257_f32.bin` (librosa-slaney).

Gated **77/77 token-exact** end-to-end vs the HF `ParakeetForTDT` reference, and again token-exact
through the Swift **CoreAIKit** `KitParakeetModel`. blank 8192 · durations [0,1,2,3,4] · 16 kHz.

<!-- gen-cards:use-it begin id=parakeet-tdt-0.6b-v3 (managed by scripts/gen-cards — edit cards.json / QuickStart.swift, not this block) -->
![Parakeet-TDT 0.6B v3 demo](https://huggingface.co/mlboydaisuke/Parakeet-TDT-0.6B-CoreAI/resolve/main/demo.gif)
*Parakeet-TDT 0.6B on iPhone 17 Pro — the zoo's coreai-audio app, real speed.*

## Use it

▶️ **Run it (source)** — the [Transcribe runner](https://github.com/john-rocky/coreai-kit/tree/main/Examples/Transcribe)
(GUI + CLI, one app for every speech-to-text model in the catalog):

```bash
git clone https://github.com/john-rocky/coreai-kit
open coreai-kit/Examples/Transcribe/Transcribe.xcodeproj
# → Run, then pick "Parakeet-TDT 0.6B v3" in the model picker

# agents / headless (macOS):
cd coreai-kit/Examples/Transcribe
swift run transcribe-cli --model parakeet-tdt-0.6b-v3 --audio sample.wav
```

💻 **Build with it** — complete; the glue is kit API, copy-paste runs:

```swift
import CoreAIKit

let transcriber = try await KitTranscriber(catalog: "parakeet-tdt-0.6b-v3")
let samples = try AudioFile.pcm16kMono(url)  // any wav/m4a/mp3 → 16 kHz mono Float
let result = try await transcriber.transcribe(samples: samples)
// result.text (25 EU languages)
```

The take-home is [`Examples/Transcribe/Sources/QuickStart.swift`](https://github.com/john-rocky/coreai-kit/blob/main/Examples/Transcribe/Sources/QuickStart.swift)
— this exact code as one typed function, no UI; both the runner's GUI and its CLI call it.
Recording? `MicRecorder` (kit API) captures mic audio as 16 kHz mono `[Float]` — the record
button and permission prompt are your app's own chrome.

**Integration checklist**

- SPM: `https://github.com/john-rocky/coreai-kit` → product **CoreAIKit**
- Info.plist: `NSMicrophoneUsageDescription` — only if you record
- Entitlements: none needed (macOS)
- First run downloads the model — 1.3 GB (Mac) — then it loads from the
  local cache (Application Support; progress via the `downloadProgress` callback)
- Measure in Release — Debug is ~3× slower on per-token host work
<!-- gen-cards:use-it end -->

## Use (CoreAIKit)

```swift
let parakeet = try await KitParakeetModel(model: .parakeetTDT)
let result = try await parakeet.transcribe(samples: pcm16kMono)   // 16 kHz mono Float
```