Qwen3-ASR 1.7B

Qwen3-ASR-1.7B is a multilingual automatic speech recognition model (~2B parameters, ~1.7B active, BF16) from Alibaba's Qwen3-ASR family that transcribes speech while identifying the spoken language across 30 languages, 22 Chinese dialects, and a range of regional English accents — and it holds up on hard audio including singing voice and songs over background music. A single unified checkpoint serves both offline and real-time streaming transcription, with word-level timestamps available via the companion Qwen3-ForcedAligner-0.6B; the Qwen team reports state-of-the-art quality among open-source ASR models and accuracy competitive with commercial APIs. This OpenASR repo repackages the original Qwen/Qwen3-ASR-1.7B weights as .oasr packs that run natively in the OpenASR runtime with no Python at inference time. For most users the q8_0 build is the recommended default — near-reference accuracy at roughly half the footprint — while q4_k suits tight-memory deployments and fp16 is reserved for verification or maximum fidelity.