Alibaba's Qwen 3.7 Max landed on Arena AI five days before the Cloud Summit and earned its spot. We tested it to see if the preview was as good as it seemed.
Alibaba’s Qwen team has unveiled Qwen3.7-Max, a flagship model built for the agent era. Unlike conventional chatbot-focused LLMs, it is designed as a foundation for autonomous AI agents that can code, debug, use tools, manage workflows, and execute long-running enterprise tasks. Alibaba claims the model can operate autonomously for up to 35 hours without performance […]
The post Qwen3.7-Max: Alibaba’s New Agent-First LLM for Coding, Reasoning, and Long-Horizon AI Workflows appeared first on Analytics Vidhya.
Alibaba's Qwen team introduced Qwen3.7-Max at the 2026 Alibaba Cloud Summit, describing it as its most advanced and comprehensive agent model to date. The model features a 1M-token context window, extended-thinking mode, and is designed for long-horizon tasks including coding, debugging, and multi-step workflow automation. It scored 56.6 on the Artificial Analysis Intelligence Index, ranking fifth overall among proprietary models.
The post Qwen Introduces Qwen3.7-Max: A Reasoning Agent Model With a 1M-Token Context Window appeared first on MarkTechPost.
Alibaba's Qwen3.7-Max could revolutionize industries by automating complex tasks, enhancing productivity, and intensifying AI competition.
The post Alibaba unveils Qwen3.7-Max, its flagship AI model for real-world tasks appeared first on Crypto Briefing.
Alibaba's strategic focus on reasoning and tool use in AI models highlights a shift towards solving complex problems, narrowing the global AI gap.
The post Alibaba’s Qwen 3.7 Max-Preview ranks 13th globally in text AI, surpassing most Western rivals appeared first on Crypto Briefing.
Alibaba has unveiled a new AI processor built specifically for AI agents, pairing the chip announcement with a multi-year silicon roadmap and a new large language model, signalling that the company is building an integrated AI stack, not just filling a gap left by US export controls. The Zhenwu M890, developed by Alibaba’s semiconductor subsidiary […]
The post Alibaba is designing AI chips around agents, and that changes what the race is actually about appeared first on AI News.
Alibaba's Qwen team has released Qwen3.5-LiveTranslate-Flash, a real-time multimodal translation model that processes audio and video simultaneously. The model covers 60 input languages and produces speech output in 29 languages at 2.8 seconds of latency. Key additions over the previous Qwen3 version include real-time speaker voice cloning, vision-enhanced comprehension via lip movements and on-screen text, and dynamic keyword configuration for domain-specific terminology. On FLEURS and CoVoST2 benchmarks, the model outperforms major commercial alternatives. It is available as an API-only model through Alibaba Cloud Model Studio using a WebSocket-based protocol.
The post Alibaba Qwen Team Introduces Qwen3.5-LiveTranslate-Flash: Real-Time Multimodal Interpretation Across 60 Languages at 2.8-Second Latency appeared first on MarkTechPost.
The post Alibaba and Tencent increase AI spending amid chip shortages appeared on BitcoinEthereumNews.com.
China’s two largest tech companies are spending substantially in AI infrastructure, anticipating that domestically produced chips will alleviate their supply problems. Alibaba Group Holding and Tencent Holdings said during recent earnings calls that they will sharply increase infrastructure spending. The companies are relying on chips made in China by Huawei Technologies and other local manufacturers to replace limited supplies of American semiconductors. Alibaba’s latest quarterly results showed a major shift in focus. For the three months ending in March 2026, the company reported very low profit. Although revenue increased slightly, Alibaba shifted spending from its main businesses to newer areas such as rapid delivery services and technology development. Profit dropped sharply, with non-GAAP net income falling from 29.847 billion yuan to just 86 million yuan. Eddie Wu Yongming
