BRIGHT EVIDENCE PACK / Deployed
Choosing when a model thinks longer.
The Qwen team released and described Qwen3, a family of dense and mixture-of-experts language models with selectable thinking and non-thinking modes.
Canonical Bright record · JSON evidence pack · Key-facts embed
Dates and assessment
- Source published
- 2025-04-29
- Bright published
- 2026-09-07
- Substantive update
- None recorded
- Evidence state
- Deployed
- Independent verification
- Not established by this source review
- Last source review
- 2026-09-07
The claim in context
The human problem
People building AI systems often need to balance response speed and cost against extra time for complex reasoning, including in multilingual work.
The prior constraint
A system's reasoning budget is often fixed or hidden from the person using it.
AI’s actual role
Qwen3 can use a slower step-by-step Thinking Mode or a faster Non-Thinking Mode; the team also reports support for 119 languages and dialects.
The documented result
Qwen announced models from 0.6B to 32B dense sizes and 30B-A3B/235B-A22B mixture-of-experts sizes, with pre- and post-trained variants available via Hugging Face, ModelScope, and Kaggle. Its source describes the two operating modes and reports multilingual support.
Why it may matter
Giving developers a stated control over reasoning time could make it easier to reserve slower processing for harder tasks and use faster responses for straightforward work.
Limitations
- The source's model rankings and language-support claims do not establish comparable accuracy or cultural fit across every listed language or task.
- The source says the family was open-sourced but this dossier does not assert a single license or complete training-data release for every variant; those must be checked per model card.
- Longer reasoning can increase latency and cost without guaranteeing a correct answer.
Original evidence
- Qwen3: Think Deeper, Act Faster · institution
Attribution
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