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AtomGradient/Qwen3-ASR-0.6B-int8-ov
Qwen3-ASR-0.6B-int8-ov is a automatic speech recognition model from AtomGradient. Use it when you need speech turned into text. It is set up for openvino. The card lists the license as apache-2.0.
Maintained by AtomGradient / 质子梯度(北京)科技有限公司.
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From the Hugging Face model README
Maintained by AtomGradient / 质子梯度(北京)科技有限公司.
Model artifacts used by AtomGradient ASR Runtime for local speech recognition on Intel hardware. The evaluated configuration uses Qwen3-ASR-0.6B with INT8 weight storage and floating-point components. INT8 does not describe every computation in the system.
| Item | Specification |
|---|---|
| Base model | Qwen3-ASR-0.6B |
| Model size class | 0.6B |
| Delivered runtime | AtomGradient ASR Runtime, supplied separately from this model repository |
| Evaluated input | 16 kHz, mono, 16-bit PCM |
| Recognition mode | Text returned after processing a complete audio segment |
| Validated device | Intel Core Ultra 5 225H, 32 GiB DDR5 |
| Evaluation focus | Chinese dialogue; public Chinese and English audio samples |
AtomGradient ASR Runtime is the local speech-recognition runtime in the AtomGradient speech delivery package. It provides model execution, recognition-request handling, cancellation and dialogue integration, using these model artifacts and third-party inference libraries.
The runtime and the model artifacts are complementary delivery components. This repository distributes the model artifacts; AtomGradient supplies the runtime, installation package and customer deployment documentation separately. The base model and third-party inference libraries retain their respective attribution.
Public audio tests on the device above, 2026-09-11:
| Sample | Audio duration | Processing time |
|---|---|---|
| Chinese | 4.204 s | 0.391 s |
| Short English | 2.461 s | 0.296 s |
| Longer English | 15.051 s | 1.378 s |
Each file was run twice. The table shows the second, warm observation, including audio preprocessing and excluding model loading. These are small-sample measurements, not latency percentiles or a general speed guarantee.
A separate AtomGradient ASR Runtime field test on 2026-09-12 completed 10 of 10 recognition requests, with median local request processing time 0.236 s and range 0.172–1.031 s. This included one wake-phrase verification and nine dialogue requests. Timing excludes the user's speaking time, audio upload and end-of-speech detection. Concurrent speech synthesis can increase recognition latency.
For deployment and integration, contact AtomGradient.
The base model is Qwen/Qwen3-ASR-0.6B. Model artifacts are distributed under Apache-2.0, following the base model's license. AtomGradient's copyright covers its own contributions and does not extend to the upstream Qwen model or third-party components.