Project AURIONAI Use-Cases Research & Innovation
reasoning

QwQ-32B-Preview

QwQ-32B-Preview is an experimental Qwen research model focused on reasoning, strong in math and coding, fine-tuned from Qwen2.5-32B-Instruct.

Alibaba (Qwen)
Levelmodel
Classreasoning
Parameters32.5B
Context32,768
Released28 Nov 2024
Opennessopen weights permissive
Runs onnot in the notes
Statuspreview

Benchmark Results

vendor-reported
vendor-reported
50
050100

Score in %. Higher is better.

28 Nov 2024 qwenlm.github.io
GPQAknowledge and reasoning
vendor-reported
65.2
050100

Score in %. Higher is better.

28 Nov 2024 qwenlm.github.io
vendor-reported
50
050100

Score in %. Higher is better.

28 Nov 2024 qwenlm.github.io
vendor-reported
90.6
050100

Score in %. Higher is better.

28 Nov 2024 qwenlm.github.io
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).

Lineage

finetune
Qwen2.5-32B-Instruct to QwQ-32B-Preview: finetune, high confidenceQwen2.5-32B-Instruct to s1: finetune, high confidenceQwen2.5-32B-InstructQwen2.5-32B-InstructAlibaba (Qwen), Sep 2024QwQ-32B-PreviewQwQ-32B-PreviewAlibaba (Qwen), Nov 2024s1s1Stanford University, Jan 2025
Alibaba (Qwen)Qwen2.5-32B-Instruct is the parent (finetune)high confidenceHugging Face base_model
Where this comes from
Parent and child relations from model cards, Hugging Face base_model fields and the genealogy tables of the research notes. The tree shows two generations each way, 3 models. Confidence and evidence are the notes' own.

R&D Topics

Identity

Developer
Alibaba (Qwen)
Family
Qwen
Released
28 Nov 2024 sourcesannouncement page
Weights published
27 Nov 2024
Record checked
11 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
dense transformer Causal transformer with RoPE, SwiGLU, RMSNorm and attention QKV bias; 64 layers; GQA 40 Q and 8 KV heads
Total parameters
32.5B sources
Active parameters
–
Checkpoint parameters
–
Note
31.0B non-embedding
Context length
32,768 tokens
Input
text
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
not in the notes
Footprint
not in the notes
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
not stated
Regional languages
not in the notes
Jakarta hosting
unknown
Languages
Card language tag: English; card warns of language mixing and code-switching
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.

Industry Use Cases

No industry use case links this model.

Sources

  1. qwenlm.github.io/blog/qwq-32b-preview https://qwenlm.github.io/blog/qwq-32b-preview/
  2. huggingface.co/Qwen/QwQ-32B-Preview https://huggingface.co/Qwen/QwQ-32B-Preview
  3. huggingface.co/api/models/Qwen/QwQ-32B-Preview https://huggingface.co/api/models/Qwen/QwQ-32B-Preview

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "QwQ-32B-Preview", https://aurion.semai.id/models/alibaba-qwq-32b-preview/, records of October 2026.