Urgent.News

What's breaking now, across thousands of outlets.

AI

Alibaba’s lightweight Qwen model takes on larger AI systems from OpenAI, DeepSeek, Zhipu

Alibaba Group Holding’s new lightweight AI model Qwen3.8-27B has matched much larger near-frontier rivals while being able to run on everyday hardware, impressing developers as local AI gains momentum. The Qwen3.8-27B, a small model with 27 billion parameters, performed on par with OpenAI’s GPT-5.6 Luna, which was billed as the most cost-efficient model in the US lab’s latest flagship series,…

Alibaba’s lightweight Qwen model takes on larger AI systems from OpenAI, DeepSeek, Zhipu

Alibaba Group Holding has introduced a lightweight AI model named Qwen3.8-27B, which has matched larger rivals such as OpenAI’s GPT-5.6 Luna and Chinese firms DeepSeek-V4-Pro-0813 and Zhipu’s GLM-5.2. The smaller model, with 27 billion parameters, was able to compete with more powerful models running on everyday hardware. Artificial Analysis Intelligence Index reported that Qwen3.8-27B outperformed GPT-5.6 mid-tier model Terra and Anthropic’s Claude Opus 4.8.

The model allows developers to run an LLM on a reasonably specced laptop, according to Simon Willison, a British programmer. While the model "defaults to wildly overthinking things" and seems slow in performance, it is a "miracle" that a 17GB file can do everything needed from an LLM for real work, Willison stated. The Qwen3.8-27B release follows a trend of smaller open-weight models becoming increasingly powerful, and global developers' interest in running AI locally on their devices is expanding.

Alibaba's Qwen models have seen over 2 billion downloads globally and are open sourced, with more than 460 models available and 3 billion downloads in total.

Written by urgent.news from SCMP Tech's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Also reported by 1 other outlet

Read the original at scmp.com →

More in AI

AI coding tools unlock small software

I’ve been programming for about 40 years. Lately, I’ve started creating new programs between meetings. The difference is that I can now hand much of the mechanical work to an AI coding tool, then…

Tokenmaxxing is out, valuemaxxing is in

It may be game over for gamified token consumption. Tesla spent six months ranking its engineers on internal AI leaderboards by token usage, then thought better of it and capped employee AI spending…

More from Tuesday 18 August →