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News

Alibaba Qwen 3.5 Launches: A New Era of Agentic AI

Sameer Katoch
Last updated: 18/02/2026
Sameer Katoch
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7 Min Read
A futuristic server room featuring a glowing digital AI interface connecting to multiple holographic screens, representing the agentic capabilities of Alibaba Qwen 3.5.

Alibaba has officially unveiled Qwen 3.5, its latest artificial intelligence model designed to power the next generation of autonomous “AI agents.” Released just ahead of the Lunar New Year, this new flagship model represents a significant pivot for the Chinese tech giant. It moves beyond simple chatbots to systems capable of executing complex tasks independently. With claims of being 60% cheaper to run and significantly faster than its predecessors, Qwen 3.5 is positioned to challenge both domestic rivals like DeepSeek and global leaders in the AI space.

Contents
Built for Action: The “Agentic” AdvantageEfficiency Through InnovationCompeting in a Crowded MarketThe Future of AI Work

The launch underscores a major shift in the artificial intelligence landscape toward “agentic AI”—systems that don’t just generate text or images but actively interact with software and devices to get work done. Alibaba’s aggressive pricing and performance claims suggest the company is eager to recapture momentum in a fiercely competitive market. By combining high efficiency with advanced reasoning, Alibaba aims to make Qwen 3.5 the foundational engine for businesses looking to automate intricate workflows without breaking the bank.

Built for Action: The “Agentic” Advantage

The defining feature of Qwen 3.5 is its focus on agency. Unlike traditional large language models (LLMs) that primarily respond to prompts, this model is engineered to function as a “visual agent.” This means it can interpret visual interfaces on computers and mobile devices, effectively allowing it to “see” screens and perform actions like a human user would. Whether it is navigating complex software menus, managing desktop applications, or executing multi-step workflows, the model is built to bridge the gap between AI reasoning and practical application.

This capability is powered by what Alibaba calls “native multimodal” architecture. The model processes text, images, and video simultaneously within a single framework, rather than relying on separate tools stitched together. This integration allows for faster, more fluid interactions. For developers, this opens up new possibilities for creating virtual assistants that can do more than just answer questions—they can book flights, organize spreadsheets, or debug code by literally looking at the problem on a screen.

Efficiency Through Innovation

Under the hood, Qwen 3.5 utilizes a sophisticated architecture known as “Mixture-of-Experts” (MoE). This design is the secret sauce behind the model’s impressive efficiency stats. While the model boasts a massive total parameter count of 397 billion, it only activates 17 billion parameters for any given query. Think of it like a massive library where you only need to consult a few specific experts to answer a question, rather than reading every book on the shelf.

This selective activation allows the model to deliver the reasoning power of a massive system while maintaining the speed and low cost of a much smaller one. Alibaba reports that this approach has resulted in an eightfold increase in processing speed compared to the previous generation. For enterprise users processing millions of tokens, this translates to substantial savings and reduced latency, making real-time AI applications far more viable.

Key Technical Specifications

  • Architecture: Sparse Mixture-of-Experts (MoE)
  • Total Parameters: 397 Billion
  • Active Parameters: 17 Billion
  • Context Window: Up to 1 million tokens (in the Plus version)
  • Capabilities: Native multimodal processing (text, vision, video)

Competing in a Crowded Market

The release comes at a critical time for Alibaba. The Chinese AI market is currently witnessing an intense “price war,” with companies slashing API costs to attract developers. By pricing the hosted version of Qwen 3.5 aggressively—reportedly around $0.18 per million tokens—Alibaba is making a direct play for market share against local competitors like ByteDance and DeepSeek. DeepSeek, in particular, made waves recently with its own efficient models, prompting Alibaba to respond quickly with a competitive alternative.

On the global stage, Qwen 3.5 is designed to rival top-tier models from US tech firms. Early benchmarks released by Alibaba claim the model outperforms leading American models in specific areas like visual understanding and instruction following. While it faces stiff competition in specialized domains like advanced mathematics and coding, the model’s strong performance in general reasoning and agentic tasks positions it as a serious contender for global enterprise adoption.

The Future of AI Work

The introduction of Qwen 3.5 signals that the industry is moving past the “chatbot” phase and into the “agent” phase. The ability to process massive amounts of context—up to 1 million tokens—means the model can ingest entire books, codebases, or legal archives and perform meaningful work on them. This large context window, combined with the ability to take action on screens, suggests a future where AI acts more like a proactive employee than a passive search engine.

For businesses, the implications are profound. The lower cost of inference removes a major barrier to entry, allowing companies to deploy AI agents in areas that were previously too expensive, such as real-time customer support or automated data entry. As the technology matures, the focus will likely shift from which model is the “smartest” to which model is the most useful and cost-effective doer of tasks. With Qwen 3.5, Alibaba has staked its claim on that practical, action-oriented future.

TAGGED: agentic AI, Alibaba, Artificial Intelligence, China tech, LLM, machine learning, Qwen 3.5, tech news
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By Sameer Katoch
As the Founder of VellaTimes and an avid traveler, I'm passionate about the daily news events happening globally. With over five years of experience in the writing field, I am committed to delivering top-notch news that satisfies your daily news intake.
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