China's Z.AI Unveils Ox Alpha, a Stealth Model That Rivals DeepSeek
Z.ai confirms Ox Alpha is a new GLM-series model and will release its weights
China's Z.AI Co., also known as Zhipu, has confirmed that its new AI model, Ox Alpha, is the latest iteration of its GLM series. The company announced it will release the model's weights tonight, responding to speculation after Ox Alpha topped online usage charts with high performance at zero cost. This move intensifies competition with DeepSeek and other AI rivals.
The company on Wednesday confirmed speculation that the Ox Alpha model is a new iteration of its GLM series and said it will release the weights for it tonight, in response to queries by Bloomberg News.
- ricardobeat
I had Ox Alpha working on coding tasks for a couple days non-stop, via OpenRouter and OpenCode Zen. Crush harness. It was able to complete tasks at a level that I'd put between Sonnet and Opus. It makes few mistakes, but is not that smart.
The main issue for me, is that it degraded into a doom loop several times. One of them was running the same bash command about a thousand times. The last model I've used that had this problem was Mimo 2.5, which is quite dated at this point. As a result of this, you cannot leave it unattended / not usable for agents.
- _pdp_
Ox Alpha has been running on auto-pilot for the past 5 days on various experiments.
Very impressive model.
Here are some examples, open-source documented and the data available in HF datasets:
https://openzot.github.io/whetstone/ - https://github.com/openzot/whetstone
https://openzot.github.io/arcade/ - https://github.com/openzot/arcade
https://openzot.github.io/machinery/ - https://github.com/openzot/machinery
- giamma
https://unwall.app/www.bloomberg.com/news/articles/2026-08-2...
- WithinReason
Mixed signals, here it's performing below even GPT-5.4 Nano:
while here it outperforms Fable by a significant margin:
but if the latter is true, will people still say it was "distilled" from Fable?
- esskay
I'd be interested to know what was going on with it during the public test as there were numerous reports of it improving considerably at tasks it was asked to do early on in the test compared to later in it.
- freakynit
It one-shotted generation of Java bindings for this project: https://github.com/jeffhajewski/latticedb
Related PR: https://github.com/jeffhajewski/latticedb/pull/5
The session used ~100K input tokens, ~60K output tokens, and ~80K thinking tokens.
I reviewed it using gpt-sol-medium, and it seems to be satisfied with it's work.
- RataNova
It writes pretty clean code and holds context alright, but it starts stumbling and losing the plot on complex bash scripts with pipelines. Waiting for the weights to drop so we can dig under the hood and see what is going on there
- harlan_pdx
Releasing weights is the right move. Keeps them competitive with DeepSeek on the open side.