DevOps / SRE / Platform · 04.08.2026, 16:03 UTC
What developers really think about Qwen3.8-Max: “An API business model wearing an open source jacket”
| Schweregrad | info |
|---|---|
| Kategorie | DevOps / SRE / Platform |
| Quelle | The New Stack ↗ |
| Veröffentlicht | 04.08.2026 UTC |
Sicherheitsmeldung mit Schweregrad noch nicht bewertet. Technische Details im Tab „Originaltext“; empfohlene Schritte in der Checkliste.
Alibaba this week announced the launch of Qwen3.8-Max. The most powerful model in the Qwen series to date, this multimodal model ships with 2.4 trillion parameters, internal variables that the model adjusts to determine reasoning as it trains.
Built upon the architectural foundation of Qwen 3.5, Qwen3.8-Max supports a context window of up to 1 million tokens, allowing it to process massive codebases or hundreds of pages of documentation to perform so-called long-horizon tasks.
The model employs a sparse mixture-of-experts design for more efficient operations and hybrid attention for memory efficiency and more efficient modeling and scaling across long contexts.
“We are officially releasing Qwen 3.8-Max, the most capable model in the Qwen family to date. This also marks the first time we will open-source the weights of a Qwen-Max-class model – the open weights will be released next week,” stated Alibaba.
What’s 400 billion parameters between friends?
Reactions to this announcement center on number of parameters, although this is not necessarily a guarantee of model competency. There’s also the question of how close Alibaba’s Qwen is to other Chinese AI frontier model competitors, including DeepSeek and Moonshot AI. Moonshot AI’s Kimi K3 arrived last month with 2.8 trillion parameters — but what’s 0.4 trillion or 400 billion parameters between friends?
Other points of interest include how it performs across core text and visual intelligence jobs, and where any new model sits on the Arena ranking leaderboard.
All of which are worthy mechanisms for kicking the tires on …