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Alibaba releases 7B-parameter Qwen Image 2.1 model, restricts commercial resale

Alibaba Cloud has launched Qwen Image 2.1, an open-weight image generation model with only 7 billion parameters, small enough to run on older consumer GPUs like the RTX 3090. The model adds native transparent-background generation and can combine up to 10 reference images into a single consistent output, and Alibaba's own benchmarks claim it outperforms closed models including Google's Nano Banana 2.0. Unlike its predecessor, the new licensing terms bar commercial resale without a separate agreement from Alibaba.

Alibaba unveils Zhenwu V900 AI chip, moves launch up to early 2027

At Apsara Conference 2026, Alibaba CEO Eddie Wu introduced the Zhenwu V900 accelerator, claiming it delivers three times the performance of the prior M890 chip and calling it China's most powerful AI chip. The V900 offers 216GB of GPU memory, 1,200GB/s inter-chip bandwidth, can scale to clusters of up to 500,000 cards, and is set for mass production in Q1 2027, earlier than the Q3 2027 date Alibaba previously targeted.

Alibaba Launches Its Most Powerful AI Chip, Plans Bigger Models Ahead

Alibaba introduced a new, more powerful AI chip as part of its strategy to control both the hardware and software underlying its artificial intelligence efforts. The company also outlined plans to build larger AI models going forward.

Alibaba unveils Zhenwu V900 AI chip, targets 20GW data center capacity by 2032

Alibaba shares rose about 3% in Hong Kong after the company revealed its next-generation Zhenwu V900 AI chip, claiming triple the performance of its predecessor released in May. At its Apsara Conference in Hangzhou, Alibaba also outlined plans to grow its cloud unit's global data center capacity beyond 20 gigawatts by 2032 and confirmed its Qwen 4 model is currently in training.

Federal Register site briefly offered Chinese Qwen3 AI model for document search

A screenshot circulated online showing the US Federal Register's search interface offering Alibaba Cloud's Qwen3:0.6B language model as a search option alongside the default semantic search. About a day after the screenshot spread, the Qwen options disappeared from the site, though an archived snapshot from September 16 confirms they existed.

Alibaba's Damo Academy open-sources Damo Radar, an AI for reading abdominal CT scans

Alibaba's research division Damo Academy has released as open source an AI vision-language model called Damo Radar, trained to interpret contrast-enhanced CT scans of 18 abdominal organs and flag around 150 conditions, including malignant tumors. Tested on nearly 40,000 real patient scans, the model reached an average diagnostic accuracy score (AUC) of 0.913 out of a possible 1.0 across 146 clinical findings.

Federal Register briefly used Alibaba's Qwen AI model, then pulled it after backlash

US officials removed a Chinese-made Qwen AI search tool from the Federal Register website on Wednesday after social media users spotted it powering search of public regulatory comments. The tool, made by Alibaba, had been live for at least a day before removal, and neither the National Archives, the White House, nor the FBI has explained how or why it was deployed.

Anthropic says China-linked actors used Claude for military targeting and torpedo defense work

Anthropic's September 2026 threat report describes Chinese-based actors using its Claude models across at least five programs, including two tied to military applications. One actor drafted fire-control specifications for an anti-torpedo system and benchmarked it against U.S. Navy systems, while another built roughly 16 software modules for suppressing enemy air defenses, with a default scenario targeting 12 sites in Taiwan such as Patriot batteries and air bases. Metadata reviewed by Anthropic suggested links to Chinese research institutions, including the PLA Academy of Military Sciences.

Chinese firm Suqiao sells modified RTX 5090 with 96GB VRAM for $3,888 on Alibaba

Shenzhen Suqiao Intelligent Technology, an established Chinese OEM/ODM, is listing a customized GeForce RTX 5090 with 96GB of memory—triple the stock 32GB—for $3,888 on Alibaba, undercutting the standard U.S. price by roughly 35%. The listing contains dubious specs like GDDR6X memory and 14 Gbps speeds, raising questions about accuracy, though the underlying GB202 chip used in Nvidia's 96GB RTX Pro 6000 Blackwell suggests such a memory configuration is technically feasible.

Anthropic says Alibaba, Moonshot, DeepSeek covertly used Claude to train rival AI models

Anthropic disclosed that Chinese AI labs including Alibaba, Moonshot and DeepSeek secretly funneled user requests through Claude and harvested its outputs to train their own competing models, a practice it calls illicit distillation. Alibaba's campaign alone involved more than 151 million exchanges between May and July, peaking near 3 million a day from over 3,500 fraudulent accounts, while Moonshot silently rerouted Kimi customer queries to Claude and presented the answers as its own.

FBI, NSA, CISA Accuse Alibaba, DeepSeek and Others of Mass-Distilling US AI Models

US federal agencies issued a joint advisory on Sept. 8 alleging that Chinese AI companies including Alibaba, DeepSeek, MiniMax, Moonshot AI, StepFun and Z.AI have run large-scale operations to pull outputs from US models like Claude, GPT, Gemini and Grok since late 2024. The advisory says these firms extracted billions of tokens through millions of queries, using techniques such as chain-of-thought extraction and automated evasion to dodge blocking measures, in order to train their own competing systems.

Tom's Hardware tests show Qwen3.8 27B struggles beyond VRAM math on RTX 5090 and rivals

Tom's Hardware benchmarked Alibaba's newly released Qwen3.8 27B open-weight AI model across discrete GPUs like the RTX 5090, RTX 4090, RTX 3090, and AMD/Intel cards, as well as unified-memory systems including the DGX Spark, Mac Studio, and Ryzen AI Halo. Despite the four-bit quantized model needing only about 17GB of VRAM, the tests found that software stacks and inference engines often bottleneck real-world performance, affecting time-to-first-token and throughput once context windows fill up.