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Storage manufacturer Nanya Technology raises DRAM contract prices again, with the maximum increase possibly reaching 20%.

1 hours ago

Beating AI Express: According to Taiwanese media reports, Taiwan-based memory manufacturer Nanya Technology has recently notified customers one after another that it will raise DRAM contract prices again, with the maximum increase possibly reaching 20%. In response to relevant market rumors, Nanya stated that it would not comment on matters related to customer quotations. Industry insiders believe that the new round of price hikes is expected to gradually pass through to the market, boosting Nanya's average selling price (ASP) and profitability. TrendForce forecasts that the overall DRAM market will remain in undersupply in the fourth quarter of 2026, with contract prices for general-purpose DRAM rising by 10% to 15% quarter-on-quarter. Consumer-grade DRAM, due to continuous production cuts by major players and its high reliance on Taiwanese manufacturers for supply, will continue to see upward price momentum. Growing AI computing power demand is continuously boosting demand for server DRAM and HBM, while advanced process production capacity is shifting toward high-performance products, further compressing the supply elasticity of traditional DRAM. Samsung, SK Hynix, and Micron have all recently been expanding or adjusting their DRAM and HBM-related production capacity and packaging layouts. Micron's CEO previously stated that amid sustained demand growth and limited new production capacity, no clear inflection point for DRAM supply-demand balance has been observed yet, and he expects HBM demand growth to remain higher than that of traditional DRAM through 2028.

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740M parameter model runs on mobile, Google’s Embedding Gemma 2 enables one-stop search for text, images, audio, and video.

Beating AI Express: Google DeepMind has open-sourced EmbeddingGemma 2. The model has just 740 million parameters, capable of directly processing text, code, images, video, and audio, and embedding all of them into a shared vector space for search and Retrieval-Augmented Generation (RAG). The previous-generation EmbeddingGemma only supported text processing. This new model allows partial loading as needed: 270 million parameters for text and code only, 440 million when adding vision capabilities, and a full 740 million parameters when all components are loaded. Google tested the model on the Pixel 11 Pro; the quantized text-only version uses as little as ~191MB of active memory, while the full version takes around 567MB. Its context window has been expanded from 2K in the prior generation to 8K, supporting processing of up to ~5.5 minutes of audio, 29 images, or 58 video frames in a single pass. The most notable improvement is in code retrieval: its MTEB Code score rose from 68.76 in the previous version to 78.68, while multilingual text performance remained largely stable, increasing slightly from 61.15 to 61.36. The model also supports reducing the default 768-dimensional vectors to 512, 256, or 128 dimensions, cutting vector storage requirements by up to one-sixth. The license has also been relaxed: while the prior EmbeddingGemma used Google’s proprietary Gemma terms, EmbeddingGemma 2 is released under the Apache 2.0 license. Gemma 4, launched by Google earlier this year, also uses Apache 2.0, reflecting a clear trend of recent open models being more business-friendly and accessible for secondary development.

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Trading app Moonshot adds support for Robinhood Chain.

According to official announcements, trading app Moonshot has added support for the Robinhood Chain, with multiple tokens including PONS, AI, and INDEX now live on Moonshot.

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Tom Lee: We are at the start of a supercycle, and all traditional finance will be tokenized within a decade.

At Token2049, Tom Lee noted that the crypto space is at the start of a supercycle, predicting that everything in traditional finance will be tokenized over the next decade. Most traditional financial institutions—including BlackRock, JPMorgan, and Robinhood—will build on Ethereum, he added. Lee also reaffirmed his bullish outlook on Ethereum (ETH) and Bitmine (BMNR) during the event. “If you’re bullish on ETH, you should also be bullish on Bitmine, which is designed to outperform core assets like BTC and ETH in this cycle. If ETH rises to $22,000, Bitmine’s stock will surge from $26 to $300–$500. If ETH hits $62,000, Bitmine will jump to $1,200–$1,500,” Lee stated.

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ETH briefly fell below $2,600, with a trader’s long position worth nearly $9.85 million fully liquidated within three minutes.

According to TradingBeats' monitoring, Ether (ETH) briefly dipped below $2,600. A long position of 3,728 ETH held by trader 0xcbab, valued at approximately $9.85 million, was fully liquidated within three minutes, incurring a loss of nearly $200,000.

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Trader 0xcbab Liquidated on $9.85M ETH Long as Price Drops Below $2,600

ETH just dropped below $2,600. Trader 0xcbab got fully liquidated on his 3,728 $ETH ($9.85M) long in just 3 minutes.

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Yi Lihua: Altcoins Undergo Broad Correction, Normal Pullback in Bull Market, No Need for Excessive Concern

Yilihua, founder of Liquid Capital, stated in a recent post that he has repeatedly warned of a potential market correction, noting Bitcoin has not yet broken below its key support level while altcoins have seen a broad-based pullback. He pointed out that he predicted a month ago Bitcoin would face a correction after rising to around $86,000. Yilihua added that a bull market spends most of its time in consolidation phases, with only a small fraction of periods marked by rapid gains and normal corrections—there is no such thing as a continuously rising bull market. He believes even if this correction is sharp, it is a normal occurrence within the bull trend, and advised investors not to try to trade constantly or seize every opportunity.

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