ReadingResearchRadarInvestment framework
Sign in / Sign up
← Back to reading
NewsTopic · 通义千问图像Turbo1 min read·2026-10-10

Alibaba Qwen Releases Qwen-Image-2.1-Turbo with 8-Step Image Generation

Alibaba open-sources an 8-step image model and launches a low-cost hosted API, cutting inference latency and hosting expenses.

ImportanceMaterialEvidenceE2 unreplicatedWrite-upStandard

Verified 2026-10-10 05:28 GMT+8

Alibaba's Qwen team released Qwen-Image-2.1-Turbo on October 9, reducing the denoising steps for image generation and editing from the base model's 40 steps down to 8.

The checkpoint retains the 7B visual generation architecture and supports native transparent RGBA output alongside multi-reference editing. Alibaba Cloud Model Studio simultaneously launched hosted APIs, pricing the Turbo version at CNY 0.1 per image with a 120 RPM limit.

The weights are distributed under the Qwen Research License, meaning commercial self-hosting requires separate permission. No independent third-party benchmarks exist yet; the vendor reports a score of 60.28 for the base model on Qwen-Image-Bench.

Sources

  • 原始出处raw.githubusercontent.com↗
Topic

通义千问图像Turbo

阿里通义千问团队于2026年10月9日正式发布并开源了Qwen-Image-2.1-Turbo模型,该模型将图像生成与编辑的推理步数从40步大幅压缩至8步,同时降低了托管成本。

Sign in / Sign up
ReadingResearchRadarInvestment framework
4 steps
1 pieces
Updated 2026-10-10 06:21

How it got here

  1. 2026-09-20阿里发布Qwen-Image-2.1基础模型,支持40步生成及多参考图编辑,Diffusers等框架Day-0支持。
  2. 2026-09-23Viggle团队发布Qwen-Image-2.1-viggle-turbo v0.1/v0.2,通过DMD蒸馏实现4-5步生成,但存在多样性损失。
  3. 2026-09-25Viggle更新v0.2.1版本,优化至6步生成,改善构图漂移,但仍建议小字渲染使用更多步数。

What is still unsettled

  • Qwen-Image-2.1-Turbo在Qwen-Image-Bench上的具体得分是多少?
  • 官方Turbo版本在复杂多参考图编辑中的表现是否优于或持平Viggle社区版?
  • 除了API调用,是否有更明确的商业授权路径供自部署用户选择?
Read the full topic →
Continue researching →