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What is Qwen 4?

Qwen 4 is Alibaba’s forthcoming next-generation foundation model and the planned successor to the company’s Qwen3.x model family. Alibaba announced Qwen 4 at the 2026 Apsara Conference on September 22 and confirmed that the model is currently in training. The company has not yet disclosed Qwen 4’s architecture, parameter count, context length, training-compute requirements, benchmark scores, pricing, licensing terms, or release schedule. Qwen 4 is being developed as Alibaba expands its broader AI stack across foundation models, multimodal systems, AI infrastructure, and agent-oriented cloud services. A major research direction surrounding Alibaba’s next generation of models is recursive self-improvement based on real-world tasks and empirical feedback. The company has already experimented with this approach using Qwen3.8-Max, allowing the model to participate in automated pipeline design, data validation, experimentation, error diagnosis, and post-training optimization. Alibaba reported that Qwen3.8-Max completed 33 iterative cycles during one such experiment and increased its Artificial Analysis score from 40 to 45. In a separate chip-design experiment, a Qwen model performed more than 10,000 EDA tool calls during over 60 hours of automated improvement work, illustrating Alibaba’s interest in long-horizon agentic tasks. These demonstrations describe the research program surrounding future Qwen development rather than confirmed features of Qwen 4 itself. Alibaba has also announced a longer-term roadmap in which Qwen 4.5 and Qwen 5 models are projected to reach between 5 trillion and 10 trillion parameters. Qwen 4 therefore remains a pre-release model, with detailed capabilities and access information expected to become clearer when Alibaba publishes its formal launch materials.

What is Qwen-7B?

Qwen-7B represents the seventh iteration in Alibaba Cloud's Qwen language model lineup, also referred to as Tongyi Qianwen, featuring 7 billion parameters. This advanced language model employs a Transformer architecture and has undergone pretraining on a vast array of data, including web content, literature, programming code, and more. In addition, we have launched Qwen-7B-Chat, an AI assistant that enhances the pretrained Qwen-7B model by integrating sophisticated alignment techniques. The Qwen-7B series includes several remarkable attributes: Its training was conducted on a premium dataset encompassing over 2.2 trillion tokens collected from a custom assembly of high-quality texts and codes across diverse fields, covering both general and specialized areas of knowledge. Moreover, the model excels in performance, outshining similarly-sized competitors on various benchmark datasets that evaluate skills in natural language comprehension, mathematical reasoning, and programming challenges. This establishes Qwen-7B as a prominent contender in the AI language model landscape. In summary, its intricate training regimen and solid architecture contribute significantly to its outstanding adaptability and efficiency in a wide range of applications.

Media

No images available

Media

Integrations Supported

Alibaba Cloud
Hugging Face
ModelScope
Python
Qwen Studio
QwenCloud
Cherry Studio
Hermes Agent
Model Context Protocol (MCP)
QwenWork

Integrations Supported

Alibaba Cloud
Hugging Face
ModelScope
Python
Qwen Studio
QwenCloud
C
C++
Clojure
HTML
Horay.ai
Julia
PHP
Ruby
Sesterce
TypeScript

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Free
Open source
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Alibaba

Date Founded

1999

Company Location

China

Company Website

qwen.ai

Company Facts

Organization Name

Alibaba

Date Founded

1999

Company Location

China

Company Website

github.com/QwenLM/Qwen-7B

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Categories and Features

AI Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

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