Project AURIONAI Use-Cases Research & Innovation
Alibaba (Qwen)
speech recognition

Qwen3-ASR-0.6B

Qwen3-ASR 0.6B variant.

Alibaba (Qwen)Alibaba (Qwen)ChinaQwen3-ASRFamily
Qwen3-ASR architecture overview: audio encoder feeding the Qwen3 language model.
Levelvariant
Classspeech recognition
Parameters600M
Contextnot in the notes
Released29 Jan 2026
Opennessopen weights permissive
Runs onsingle datacentre GPU, CPU server
Statusactive

Benchmark Results

vendor-reportedmaintainer-run
FLEURSspeech
FLEURS Indonesian, Table A.2vendor-reported
7.92
048

Score in WER. Lower is better.

Qwen3-ASR technical reportJan 2026 arxiv.org
Hugging Face Open ASR Leaderboardspeech
eight-set macro-average English WERmaintainer-run
6.42
048

Score in WER. Lower is better.

snapshot 2026-05-06 via benchmarklist6 May 2026 benchmarklist.com
Where this comes from
Every score names who ran it: vendor-reported, maintainer-run or independent. A rank is shown with the population it was ranked in (gap rule 3).

R&D Topics

Audio language models for speech understandingproduced by

Identity

Developer
Alibaba (Qwen)
Family
Qwen3-ASR
Released
29 Jan 2026 sourcesannouncement page
Weights published
–
Record checked
10 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.

Architecture and Size

Architecture
autoregressive
Total parameters
600M sources
Active parameters
–
Checkpoint parameters
–
Context length
not in the notes
Input
audio
Output
text
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).

Openness and Access

Openness
open weights permissive
Licence
Apache License 2.0 sources
Access routes
open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.

Deployment

Runs on
single datacentre GPU, CPU server
Footprint
CPU-feasible (judgement)
Runtimes
not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.

Indonesia

Indonesian support
measured on a benchmark
Regional languages
not in the notes
Jakarta hosting
unknown
Languages
not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.

Lineage

The notes record no lineage for this model.

Industry Use Cases

No industry use case links this model.

Sources

  1. Gladia - Best open-source speech-to-text models in 2026 gladia.io https://www.gladia.io/blog/best-open-source-speech-to-text-models
  2. Open ASR Leaderboard Benchmark Scores & AI Model Leaderboard | BenchmarkList benchmarklist.com https://benchmarklist.com/benchmarks/open_asr_leaderboard/
  3. Qwen3-ASR Technical Report arxiv.org https://arxiv.org/html/2601.21337v2

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Qwen3-ASR-0.6B", https://aurion.semai.id/models/alibaba-qwen3-asr-0-6b/, records of October 2026.