AIToday
Large Language ModelsOpen-Source AISiliconANGLE AIPublished: Aug 27, 2026, 10:03 JST

Z.ai open-sources GLM-5.3-Flash, 10x cheaper to run

Z.ai open-sources GLM-5.3-Flash, 10x cheaper to run

3 Key Points

  1. What happened

    Z.ai Co. released the code for GLM-5.3-Flash, an LLM with 320 billion parameters that activates 18 billion per prompt. It first appeared last week on OpenRouter Inc. as an unnamed free model called Ox Alpha, which drew industry attention.

  2. Why it matters

    The model costs ten times less to run than Z.ai's previous-generation LLM. It uses sparse attention and linear attention to cut processing power and memory, and it scored highest on the GDPval-AA v2 benchmark against Claude Opus 4.8, GPT-5.6 Terra and Gemini 3.7 Flash.

  3. What to watch

    GLM-5.3-Flash accepts up to 1 million tokens of input (text, images, video) and generates up to 131,072 tokens. Its weights are available on Hugging Face.

Not sure about something? Ask the AI

Questions and answers are published on this page.

Summaries like this, in your inbox every morning.

Context & Analysis

Z.ai's open-sourcing of GLM-5.3-Flash follows the model's debut on OpenRouter as 'Ox Alpha' without a named developer, a move that sparked speculation and attention. The company has now confirmed its authorship and released the weights publicly on Hugging Face.

The release emphasizes cost efficiency, a key factor for businesses deploying AI at scale. The company states the model costs ten times less to run than its prior generation, achieved through architectural changes including sparse and linear attention mechanisms that reduce processing and memory demands.

Benchmark results place GLM-5.3-Flash competitively, with the highest score on GDPval-AA v2 against Claude Opus 4.8, GPT-5.6 Terra, and Gemini 3.7 Flash, and second place on AutomationBench. Training used a 30 trillion token dataset and a technology called mHC to reduce gradient distortion.

FAQ
What is OpenRouter's connection to this model?
OpenRouter Inc. launched a free hosted version of the model last week under the codename Ox Alpha and did not disclose its developer, which led users to speculate that Z.ai was the creator.
How does GLM-5.3-Flash reduce hardware requirements?
It uses sparse attention, which reviews only the most relevant tokens instead of every token, and linear attention, which substitutes the softmax algorithm so that doubling prompt size only doubles RAM usage instead of quadrupling it.
SiliconANGLE AIRead Original Article

AI news that matters for your work, delivered every morning.

Pick your industry and the AI tools you use, and get news related to your work every day.

Free · 30 seconds with Google · unsubscribe anytimeWhat is AIToday? →

Ask AI

Ask AI anything about this article. The AI reads this article, earlier AIToday articles, and Wikipedia, and cites its sources. Q&As are published on this page for other readers too.

Questions and answers are published on this page.

Related Articles

Next articleTesla's AI5 chip claims 2-3x Nvidia efficiency