Memory stocks drop 8% to 10% as NASDAQ pullback hits semiconductors

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[1] Micron Drops 8%, SanDisk Slumps 10%, Western Digital Falls 7% as Memory Stocks Pull Back With the NASDAQ (https://247wallst.com/investing/2026/07/01/mi ...)[2] Micron Stock Price Prediction: After a 4x First Half, the Forecast Flashes Sell (https://247wallst.com/investing/2026/06/30/mi ...)[3] 3 Market Predictions For July (https://seekingalpha.com/article/4918876-3-ma ...)[4] Nasdaq, Dow Futures Kick Off July in The Red (https://www.schaeffersresearch.com/content/ez ...)

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Jul 16 2026, 19:29

Google Gemini 3.5 Pro delayed months, shares drop 5% on report

**Alphabet's most powerful AI model is months behind schedule as internal benchmarks show it trailing Anthropic and OpenAI on coding tasks.** Google's Gemini 3.5 Pro, its flagship AI model, has fallen months behind schedule as engineers struggle to improve coding capabilities, according to a Bloomberg report that sent Alphabet shares down 5% on Thursday. "The delay has been a source of frustration for Google engineers, AI researchers and managers, many of whom are concerned the company risks losing an edge in the market," 10 current and former employees told Bloomberg's Julia Love and Davey Alba. The company has multiple layers of stakeholders involved in preparing models for release, working to weave AI across a vast product portfolio including search, maps and YouTube, which can cause delays, the people said. Rivals Anthropic and OpenAI have produced models that exceed Gemini's capabilities in key areas, according to the employees. The setback threatens Google's position in a market where Alphabet has committed more than $80 billion in AI investments, including a landmark deal with Berkshire Hathaway. Alphabet shares closed down 5% on the news, erasing billions in market value. The coding deficiency is particularly concerning because it strikes at the heart of enterprise AI adoption. Software developers represent one of the largest paying customer segments for large language models, and coding benchmarks such as HumanEval and SWE-bench have become standard measures of model capability. Google's inability to match competitors on these metrics could slow enterprise adoption of its cloud AI services, a business that competes directly with Microsoft-backed OpenAI and Amazon's Bedrock platform. **Internal Pressure Mounts as Competition Intensifies** The delay reflects a broader challenge inside Google: balancing the speed of AI development with the safety and integration requirements of a company whose products reach billions of users. While startups like OpenAI and Anthropic can ship models with fewer internal approvals, Google must ensure its AI works reliably across search, advertising, YouTube and cloud — each with its own engineering team, safety standards and product timeline. Anthropic's Claude 4 and OpenAI's GPT-5 have both set new benchmarks in coding and reasoning over the past six months, according to published evaluation scores. Google's Gemini 2.0, the predecessor to the delayed 3.5 Pro, trails on several key metrics, putting pressure on the company to deliver a model that can reclaim the technical lead. **What's at Stake for Investors** Alphabet trades at about 22 times forward earnings, a discount to Microsoft's 30 times but a premium to many legacy tech peers. The Gemini delay raises questions about whether Google can monetize its AI investments as quickly as rivals. Microsoft has already integrated GPT-5 into its Azure OpenAI Service, GitHub Copilot and Microsoft 365 suite, generating measurable revenue from AI features. Google's ability to do the same depends on shipping competitive models. The company has not disclosed a revised release date for Gemini 3.5 Pro. Analysts expect an update at Google's next major developer event, though the timeline remains uncertain. This article is for informational purposes only and does not constitute investment advice.

Jul 16 2026, 19:29

Moonshot AI launches 2.8 trillion parameter open-source Kimi K3 to challenge Anthropic

**Kimi K3 is the largest open-weight AI model ever released, directly challenging Anthropic's closed-source Claude Opus 4.8.** Moonshot AI's Kimi K3, a 2.8 trillion-parameter open-weight model, matches or beats Anthropic's Claude Opus 4.8 on key benchmarks while costing a fraction to deploy, threatening the US lab's pricing power. "Kimi K3 closes the gap between Chinese open-source models and the best closed-source systems to a degree that challenges the prevailing 8-to-12-month lag narrative," a person familiar with the company's internal positioning told the Financial Times. The model uses a mixture-of-experts architecture with 2.8 trillion total parameters and a 1 million-token context window, compared with an estimated 1.5 trillion to 2 trillion for Opus 4.8. On SWE-bench Verified, LiveCodeBench, Tau2 for agent tasks, and AIME for math reasoning, Kimi K3 reached leading open-source levels and approached or matched top closed-source models, according to Moonshot AI's published results. The timing amplifies the competitive pressure. Anthropic plans to raise Opus 4.8 prices by about 50% starting September, to $3 per million input tokens and $15 per million output tokens. Moonshot AI's earlier K2.6 model cost roughly one-third of Opus 4.8. If Kimi K3 follows a similar pricing curve, enterprises running large-scale inference workloads could see cost savings in the millions annually by switching. The open-weight release — developers can download, deploy, and fine-tune the model freely — mirrors the strategy that propelled DeepSeek to global prominence. DeepSeek is now raising funds at a roughly $71 billion valuation, while Moonshot AI is in the process of raising capital at about $31.5 billion. By comparison, Anthropic's latest fundraising round valued it at $96.5 billion and OpenAI at $85.2 billion. **The Pricing Gap Widens** The cost differential is the most immediate threat to US AI labs' business models. Anthropic's planned 50% price increase for Opus 4.8 comes as Chinese competitors push costs lower. DeepSeek's R1 series already demonstrated that open-weight models can undercut US pricing while maintaining competitive capability on many tasks. Marc Andreessen, co-founder of Andreessen Horowitz, said Chinese AI lab Zhipu's GLM-5.2 had become the first Chinese model to match or lead US flagship models on several public benchmarks. Kimi K3 has not yet published official benchmark results against Anthropic's unreleased Fable model, which was paused over safety concerns. According to industry estimates, Fable remains decisively ahead on raw capability. But Kimi K3 wins on price "by an order of magnitude" and on openness outright, according to one analysis. The model's 1 million-token context window — four times the size of GPT-4's standard context — makes it particularly suited for long-horizon software engineering tasks, a use case where enterprises have traditionally relied on closed-source models. **What This Means for Investors** For investors, the key question is whether US AI labs can maintain pricing power as open-weight alternatives improve. Nvidia, whose GPUs power most AI training and inference, benefits from increased model-building activity regardless of which company wins. But Anthropic and OpenAI face pressure to justify premium pricing when free, competitive alternatives exist. Moonshot AI's $31.5 billion valuation target and DeepSeek's $71 billion target suggest the market is already pricing in a shift toward open ecosystems that could reshape the AI industry's revenue model. The Financial Times reported that more Silicon Valley investors and tech executives now believe the real competitive battleground is developer ecosystems, not benchmark scores. This article is for informational purposes only and does not constitute investment advice.

Jul 16 2026, 19:27

Alphabet drops 5% as Google Gemini AI model faces delay

**Google's delayed Gemini AI model threatens Alphabet's competitive position against OpenAI and Microsoft just days before its Q2 earnings report.** Alphabet shares fell 5% on July 16 after a media report that Google's next-generation Gemini AI model will be delayed, raising questions about the company's competitive standing in the $200 billion-plus AI market. "The delay comes at a critical moment when every week of lost time cedes ground to OpenAI and Microsoft," said Dan Coatsworth, head of markets at AJ Bell trading group. The selloff pushed Alphabet's stock roughly 12% below its 52-week high of $408.61, paring its year-to-date gain to about 14%. The company is scheduled to report second-quarter results on July 22, with analysts projecting earnings per share of $2.87, up 24% from a year earlier, on revenue of roughly $116.5 billion. The Gemini delay threatens to slow the conversion of Alphabet's $462 billion cloud backlog — nearly double the prior quarter — into revenue at a time when Google Cloud is the company's fastest-growing segment, expanding 63% year over year to $20.03 billion in the first quarter. **Cloud Revenue at Stake** Google Cloud has emerged as Alphabet's primary growth engine, crossing the $20 billion quarterly revenue threshold for the first time in Q1. Management said just over half of the $462 billion backlog should convert to revenue over the next 24 months. A delayed Gemini model could slow enterprise customers' willingness to commit to Google's AI-powered cloud services, potentially pushing revenue recognition into 2027 and beyond. The competitive pressure is intensifying. Amazon committed an additional $13 billion last month for AI and cloud infrastructure in India, while Microsoft's partnership with OpenAI continues to capture enterprise AI workloads. Alphabet itself is investing heavily, with capital expenditure guidance raised to $180 billion to $190 billion, including a $14.5 billion data center project in Andhra Pradesh, India. The Wiz acquisition, now reported within Google Cloud, is expected to create a low single-digit percentage-point headwind to the segment's operating margin for the remainder of 2026. Alphabet will also begin recognizing a small amount of TPU hardware revenue later this year as it starts delivering chips directly into select customer data centers, with the majority of that revenue expected in 2027. **Earnings Test Looms** The July 22 earnings report will be the first clear read on whether the Gemini delay has affected near-term demand. Alphabet has beaten consensus earnings estimates in each of the past four quarters, including Q1's blowout when earnings per share of $5.11 crushed expectations and revenue growth of 22% was the fastest since 2022. Fifty-four analysts rate the stock a Moderate Buy, according to data compiled by Bloomberg. A clean print on Cloud and Search could push shares toward record highs, but any sign that the Gemini delay is weighing on cloud deal flow could extend the selloff. Alphabet trades at roughly 22 times forward earnings, a discount to Microsoft's 30 times, reflecting the market's uncertainty about the company's AI trajectory. This article is for informational purposes only and does not constitute investment advice.