Qwen 4 Is Coming: What's Confirmed and What It Means
Alibaba confirmed at the Apsara Conference in Hangzhou that Qwen 4 is in training, highlighting the 27B tier for local AI deployments.

Stock photo for illustration only, not from the actual event
- Alibaba confirmed at the Apsara Conference in Hangzhou that Qwen 4 is currently in training.
- Community timing signals point toward a launch within weeks rather than months.
- The 27B model tier remains a major focus for local AI enthusiasts running single consumer GPUs.
- Flash-Next previews new architectural shifts focusing on agentic tasks and coding capabilities.
Alibaba officially confirmed during the Apsara Conference held on September 22, 2026, in Hangzhou, China, that the Qwen 4 family is currently undergoing training. Qwen lead Liu Dayiheng described the upcoming release as being built on a new-generation architecture arriving very soon, though specific dates, technical specifications, benchmark results, and licensing terms were not disclosed.
Widely cited figures of 5 to 10 trillion parameters refer to the longer-term roadmap for Qwen 4.5 and Qwen 5, rather than confirmed specifications for Qwen 4. The current flagship model, Qwen3.8-Max, is a Mixture of Experts model boasting approximately 2.4 trillion parameters with roughly 95 billion active parameters and a 1-million-token context window.

Stock photo for illustration only, not from the actual event
Regarding release timelines, community threads, tracker pages, and prediction markets like Manifold price a launch before November 1, 2026, at roughly 74%, signaling a matter of weeks rather than months. This follows the precedent set by Qwen3.8, where the flagship Max launched on August 3 and open weights for the 27B version appeared on Hugging Face roughly ten days later.
Another notable element is the Flash-Next architecture preview, which shipped ahead of the flagship model, suggesting Alibaba is decoupling the architecture announcement from the full model rollout. The current Qwen3.8-27B is a dense vision-language model featuring robust repository-level coding and instruction-following capabilities under the Apache 2.0 license.
"Built on a new-generation architecture and arriving very soon."
Liu Dayiheng
The 27B model category serves as a sweet spot for local AI deployments, balancing near-frontier capabilities with hardware requirements suitable for consumer-grade graphics cards. Evaluating how Qwen 4 optimizes token usage and quantization will be crucial for self-hosting enthusiasts seeking efficient local inference.
For practical hardware deployment, quantized versions of these models remain essential, allowing users to run complex workloads efficiently while maintaining high performance across coding and general knowledge tasks.
Source: Dev.to
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