Alphabet faces earnings concerns amid Gemini delay and spending worries
Google's parent company saw its stock drop over 4% after reports that its Gemini 3.5 Pro AI model missed its launch window, raising questions about whether Big Tech's massive AI bets are paying off.
+15.1% (FY ended 2025-12-31 vs FY ended 2024-12-31) 10-K
Annual net income
132,170,000,000 USD (FY ended 2025-12-31, attributable to the company) 10-K
Annual operating margin
32.0% (FY ended 2025-12-31)
Forward P/E
Unavailable: no dated forecast source
Gloria daily close for session Oct 29, 2026. Market cap and trailing P/E use this close with the SEC share total and trailing diluted earnings, each dated next to its figure. Annual revenue, revenue growth, net income and margin show their own fiscal period and link the 10-K. Current context may postdate this article.
Alphabet Inc. and its peers
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Price
Market cap
P/E (trailing)
Forward P/E
Annual revenue (USD)
Annual revenue growth
Annual net income (USD)
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Alphabet Inc.
GOOGL · Price dated Oct 29, 2026 · tokenized GOOGLx
3,333,751,000FY ended 2025-12-31, attributable to the company · 10-K
75.8%FY ended 2025-12-31
Missing figures stay unavailable. Forward P/E requires a dated source. Annual revenue, revenue growth, net income and margin come from each company's own 10-K, in US dollars, and each row shows that fiscal year. Revenue growth compares the fiscal year with the prior year stated in the same 10-K. Net income is the full year amount attributable to the company, or available to common stockholders where the filing states only that, or consolidated net income. Each row names its basis. Trailing P/E reads "Not meaningful" when the dated trailing diluted EPS is a loss or zero. An operating margin appears only when the filing states both the operating income and the revenue for the same year.
Sources: SEC filings, Gloria daily closes and CoinGecko. Oldest record refresh: Oct 29, 2026, 12:56 PM EDT. Refresh is not a price or filing date. Each row shows its price date and its annual fiscal period. Peers use industry code and company size, or editorial selection. Market cap multiplies that row price by the company share total the latest SEC filing states for every share class together. Trailing P/E divides it by trailing diluted earnings from SEC filings. Rolled earnings per share are approximate because share counts can change between periods. Both appear only when the SEC data carries its date, so they are estimates at one price date, not synchronized filing valuations. Not investment advice.
Token vs underlying stock
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Alphabet token vs Alphabet stock: exact source values
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Alphabet promised its next-generation AI model would be ready by late June. It’s mid-July, and the model still isn’t here.
A Bloomberg report on July 16 revealed that the launch of Gemini 3.5 Pro has been delayed after developers found the model’s coding performance fell short of expectations during training. The news sent Alphabet’s stock tumbling more than 4% in after-hours trading, adding fresh anxiety ahead of the company’s second-quarter earnings report scheduled for July 22.
The $190 billion question
Here’s the thing about Alphabet’s AI ambitions: they are staggeringly expensive. The company’s capital expenditure guidance for 2026 sits at $180 to $190 billion. For context, that’s roughly double the $91.45 billion it spent in 2025.
CEO Sundar Pichai had previously flagged supply-chain issues, power constraints, and compute limitations as obstacles to scaling Alphabet’s AI infrastructure.
The July 22 earnings call will need to offer concrete timelines and monetization roadmaps. Investors watching the call should pay close attention to two things: whether Alphabet provides a revised timeline for Gemini 3.5 Pro, and whether the company adjusts its capex guidance downward or doubles down on the $180 to $190 billion figure.
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OpenAI and Anthropic have both been aggressively shipping competitive models. Every week that Gemini 3.5 Pro remains unreleased is a week where enterprise customers and developers deepen their integrations with rival platforms.
The disappointing training results that triggered the delay are particularly concerning. Coding performance is one of the most commercially valuable benchmarks for large language models, driving adoption among software developers and enterprises automating technical workflows.
What this means for crypto-native AI plays
There’s no direct crypto angle in Alphabet’s Gemini delay. No tokens were mentioned. No protocols are involved.
Pichai’s own admissions about power constraints and compute limitations are exactly the problems that decentralized GPU networks and distributed training protocols claim to address.
When Alphabet drops 4% after hours, it drags broader tech sentiment with it. And tech sentiment, for better or worse, still correlates meaningfully with risk-asset appetite across crypto markets.
Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our Editorial Policy.
