Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Qwen3.8-Flash-Next represents an open-weight multimodal Mixture-of-Experts architecture and serves as an initial glimpse into the design intended for Qwen4. This model strategically enhances attention mechanisms, residual pathways, embeddings, and optimization techniques to boost its capabilities, improve computational efficiency, expand model capacity, and ensure training stability. Its innovative hybrid architecture merges Gated DeltaNet, which adeptly compresses past information, with Qwen Sparse Attention, enabling the selection of significant context at a micro-block level to lessen both attention and indexing costs associated with lengthy sequences. The Gated Residual feature broadens the residual pathway into four streams, dynamically managing the flow of information across different layers. Additionally, the N-gram Embedding integrates large-scale local-pattern memory with minimal added computation per token, and it can be transferred to host memory for further efficiency. The model is structured around a 125B-parameter main network supplemented by 51B parameters dedicated to N-gram embeddings, activating only 6B parameters for each token processed. This sophisticated framework highlights the ongoing advancements in machine learning architectures, setting a promising stage for future developments.
Description
Qwen 4 is the upcoming fourth-generation foundation model in Alibaba’s Qwen AI family. Alibaba publicly confirmed at its 2026 Apsara Conference that the model is currently being trained. The company has not yet released technical specifications, model weights, API access, pricing, benchmark results, or a launch date for Qwen 4. Its development forms part of Alibaba’s broader effort to advance foundation models capable of increasingly complex and long-horizon work. The Qwen team is also researching recursive self-improvement, in which models use empirical feedback to identify weaknesses, design experiments, evaluate results, and iteratively improve training processes. Alibaba demonstrated this approach with Qwen3.8-Max, which completed 33 automated optimization cycles during a month-long experiment and improved its Artificial Analysis score from 40 to 45. These experiments provide context for Alibaba’s model-development direction but do not establish specific Qwen 4 capabilities. Alibaba has additionally outlined Qwen 4.5 and Qwen 5 models that could eventually scale to between 5 trillion and 10 trillion parameters. Until Qwen 4 is released, its exact architecture, modalities, performance, deployment options, and licensing remain to be announced.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
Alibaba Cloud
Alibaba Cloud Model Studio
Cherry Studio
Cline
ClinePass
Happy Shrimp 1.0
Hermes Agent
Hugging Face
Model Context Protocol (MCP)
Novita AI
Integrations
Alibaba Cloud
Alibaba Cloud Model Studio
Cherry Studio
Cline
ClinePass
Happy Shrimp 1.0
Hermes Agent
Hugging Face
Model Context Protocol (MCP)
Novita AI
Pricing Details
$2 per 1M (input)
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Alibaba
Founded
1999
Country
China
Website
qwen.ai/blog
Vendor Details
Company Name
Alibaba
Founded
1999
Country
China
Website
qwen.ai