---
license: apache-2.0
language:
- multilingual
pipeline_tag: automatic-speech-recognition
tags:
- core-ai
- apple
- on-device
- asr
- qwen3
---

# Qwen3-ASR-1.7B — Core AI

Qwen3-ASR-1.7B speech-to-text converted for Apple **Core AI**, running on-device (iPhone + Mac).
The zoo's first ASR model: an AuT audio encoder feeding a Qwen3 decoder on the pipelined engine
(audio embeds bound to one static input buffer; `{lang}<asr_text>{text}` output). ≤30 s clips,
52 languages, automatic language detection.

<!-- gen-cards:use-it begin id=qwen3-asr-1.7b (managed by scripts/gen-cards — edit cards.json / QuickStart.swift, not this block) -->
## 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 "Qwen3-ASR 1.7B" in the model picker

# agents / headless (macOS):
cd coreai-kit/Examples/Transcribe
swift run transcribe-cli --model qwen3-asr-1.7b --audio sample.wav
```

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

```swift
import CoreAIKit

let transcriber = try await KitTranscriber(catalog: "qwen3-asr-1.7b")
let samples = try AudioFile.pcm16kMono(url)  // any wav/m4a/mp3 → 16 kHz mono Float
let result = try await transcriber.transcribe(samples: samples)
// result.text, result.language (52 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 — 3.1 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 -->

Driven by [CoreAIKit](https://github.com/john-rocky/coreai-kit) `KitASRModel`:

```swift
let asr = try await KitASRModel(model: .qwen3ASR1_7B)
let r = try await asr.transcribe(samples: pcm16kMono)   // -> (language, text)
```

Layout: `gpu-pipelined/` holds the decoder bundle (`*_decode_int8hu_n390_s1`, int8) + the paired
AuT encoder (`*_audio_encoder_fp16_k30`, fp16). Same bundles on iOS and macOS.

App: [coreai-audio](https://github.com/john-rocky/coreai-model-zoo/tree/main/apps/coreai-audio)
(Transcribe tab — pick Qwen3-ASR or Whisper large-v3-turbo). Card:
[zoo/qwen3-asr.md](https://github.com/john-rocky/coreai-model-zoo/blob/main/zoo/qwen3-asr.md).