China's Z.AI Ships GLM-5.3, Calling It the Top Open-Weight Coding Model
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JPMorgan: Open source weight commercialization exhibits a "winner-takes-all" phenomenon; Zhipu target price raised to HK$2,000, MiniMax target price cut to HK$300.
According to BlockBeats, on July 8th, JPMorgan Chase released a research report stating that currently competitive models in the market can expand adoption through open-source weighting and continue to monetize through official APIs, partner channels, enterprise deployments, and workflow products; while weaker models face faster price comparisons and traffic fragmentation. JPMorgan Chase raised its revenue forecasts for Zhipu from 2026 to 2030 by 3% to 9%, and narrowed its adjusted loss forecasts for 2026 and 2027 to RMB 3.711 billion and RMB 3.141 billion respectively. The 2028 forecast was revised from a loss of RMB 1.287 billion to a profit of RMB 2.367 billion. The target price was raised from HKD 1800 to HKD 2000, maintaining an "Overweight" rating. The report believes that the performance of GLM-5.5/6, KimiK3, and DeepSeekV4.1 will be key indicators of whether Zhipu can maintain its leading position. JPMorgan lowered its revenue forecasts for MINIMAX-W (2027-2030) by 2% to 8%, and reduced its target price from HK$400 to HK$300, while maintaining a "neutral" rating. The company noted that the M3 model offers a permanent 50% discount, reflecting that the model has not yet created a significant capability premium for leading domestic competitors. JPMorgan believes that if MiniMax can narrow the capability gap, normalize the discount, maintain API usage, and demonstrate stronger workflow stickiness through MiniMaxCode, its outlook could turn positive.
Some large-scale AI models in China are 90% cheaper than those in the US; Chinese AI's high cost-effectiveness is capturing the US market.
According to a report by CNBC on July 7th, influenced by the continued price increases of models from leading US AI vendors, Chinese AI large-scale models are rapidly expanding their application scale in US enterprises due to their cost-effectiveness advantage. Industry insiders point out that the performance of some leading open-source and open weighted models in China is currently about 6 to 9 months behind the technology of top-tier US models such as OpenAI and Anthropic, while the price is 60% to 90% lower, and they can cover the vast majority of routine AI tasks, thus gaining popularity among US enterprises. According to statistics from the AI model aggregation platform OpenRouter, since February 8th of this year, the proportion of Chinese AI models used by US enterprises has exceeded 30% weekly, reaching a peak of 46%; while the average proportion in the previous 12 months was 11%. Another industry statistic shows that in the first week of the launch of Zhipu's latest large-scale model GLM 5.2, the daily average number of word calls increased by 27 times and the number of customers increased by 80 times, making it the fastest-deployed model on the platform in 2026; US AI startup Lindy has significantly reduced costs after switching all its AI business to DeepSeek models, and expects to save millions of dollars within a few months. (CCTV Finance)
The Payment & Clearing Association of China issued a warning to prevent cross-border gambling fraud involving virtual currency top-ups.
Odaily Odaily reports that the Payment & Clearing Association of China has issued a warning about preventing cross-border gambling scams involving virtual currency top-ups. The aim is to help the public raise their awareness of fraud prevention and gambling resistance, and improve their ability to identify and combat scams. The Association reminds the public that cross-border gambling is a losing proposition, and participating in gambling through virtual currencies is more concealed and risky. Participating in gambling or providing fund settlement services for gambling activities are illegal and violate regulations. Do not participate in virtual currency gambling transactions and safeguard your financial security.
South Korean semiconductor stocks saw a pullback, but Gate SKHYNIX futures contracts remained among the top open interest in the sector.
According to ChainCatcher, Gate, the only platform exclusively supporting Korean stock trading, continues to enrich its global equity asset portfolio. Recently, the Korean semiconductor sector has experienced increased volatility, but market trading activity remains high. According to the latest data from the Gate platform, semiconductor leader SK Hynix reached a high of $1654.1 and a low of $1509.9 during today's trading session, currently trading at $1543.1, a daily decrease of 5.03%. According to CoinGlass data, Gate's SK Hynix (SKHYNIX) contract open interest exceeds $24.5448 million, ranking among the top in the industry.
Meituan open-sourced its trillion-parameter large-scale model LongCat-2.0, and simultaneously released the inference code for domestically developed Chinese card processors.
According to Beating's monitoring, Meituan has officially open-sourced its trillion-parameter large-scale model, LongCat-2.0, with a total of 1.6T parameters and an average activation of approximately 48B, designed specifically for real-world agentic coding tasks. Architecturally, it innovatively introduces LongCat sparse attention and N-gram embedding. The former reduces fragmented memory access through flow-aware indexing and hierarchical indexing, accelerating training and inference with millions of contexts; the latter, while achieving nearly 97% sparsity in MoE, invests 135B parameters into the embedding layer, balancing parameter gains and structural stability. Post-training employs multi-teacher online distillation, categorizing experts into Agent, Inference, and Interaction types, seamlessly integrating them on a domestic computing power cluster through the MOPD architecture. As the industry's first trillion-parameter model to complete inference on a 50,000-card domestic computing power cluster, LongCat-2.0 validates the mature capability of domestic chips to handle complex large-scale model tasks. To address the multiple limitations of domestically produced Chinese chips in terms of memory, bandwidth, and interconnects, Meituan has made breakthroughs in three areas: model, chip adaptation, and deployment. At the model level, ScMoE leverages the core control capabilities of domestically produced chips to achieve physical core-level parallelism for Dense and MoE branches, combined with KV-cache partitioning to alleviate the pressure on ultra-long context memory. At the chip adaptation level, Super Kernel reduces operator startup overhead, and Weight Prefetch hides I/O latency, maximizing hardware utilization under constrained conditions. At the deployment level, PD separation is adopted to balance TTFT and TPOT, along with asynchronous Expert-Parallel load balancing to solve load unevenness under high EP (efficiency level). This open-source release simultaneously provides multiple precision versions, including BF16, FP8, and INT8, and fully opens up inference results optimized for domestic computing power, aiming to enable existing domestically produced cards and even older cards to smoothly deploy trillion-model inference services. --------------------------------- Click the original link below to join the Beating · Lark AI news channel and monitor global AI hot topics and news 24/7.
This morning, an address opened a 20x long position of 600 BTC, becoming one of the top 6 BTC positions on Hyperliquid.
PANews reported on July 6th that, according to on-chain analyst Ai Yi, address 0x004…c1bb8 opened a 20x long position of 600 BTC at 8:30 AM this morning, worth $38.07 million, becoming one of the top 6 BTC positions on Hyperliquid. The entry price was $63,476. The stop-loss and take-profit orders were set as follows: take profit on 200 BTC at $65,000, take profit on 100 BTC at $66,000, and stop-loss on 200 BTC at $60,000.