+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 27, 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
Company
Price
Market cap
P/E (trailing)
Forward P/E
Annual revenue (USD)
Annual revenue growth
Annual net income (USD)
Operating margin
Alphabet Inc.
GOOGL · Price dated Oct 27, 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 28, 2026, 4:51 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
Current comparison for GOOGL. Historical observations may postdate this article.
Split-adjusted regular-session stock closes from the existing Gloria shared history, paired only with an observed token price within 45 minutes of 16:00 New York time. Up to 60 matched sessions. No interpolation or missing-date fill. Weekends and known early closes are omitted. Token units are not adjusted for issuer multipliers or dividend treatment. This compares quoted prices, not fair value, executable premiums or arbitrage returns. Solid line: token. Dashed line: stock. Exact quote times and values appear below. Historical observations. Retrieval refers to the token source. Token quote times use UTC. The fixed cohort shows its oldest member fetch.
Alphabet token vs Alphabet stock: exact source values
Quoted token and share units can have different rights, multipliers and dividend treatment. This is not an executable premium or arbitrage signal.
Human oversight of artificial intelligence systems can fail when reviewers lack the time, context and authority needed to identify subtle errors, Bloomberg reported.
Former Google DeepMind researchers Rishub Jain and Joshua Jacob have raised $6.5 million to build a hybrid human-AI “judge” intended to oversee models and reduce the risk of them going rogue.
Their nonprofit, Sampura Research, is based on work suggesting that human-AI oversight can outperform AI-only systems, although the improvement was modest. The researchers plan to compare their system with AI-only models and human reviewers working alone.
A DeepMind employee told Bloomberg that engineers and researchers are spending less time understanding code and more time verifying AI outputs. The employee said pressure to move quickly could erode the careful review needed to detect hidden errors.
AI, tech, and the markets they move—in one daily briefing.
Daily. Free. Join 34,000+ readers across crypto, finance, and policy.
More than 1,100 employees at OpenAI, Anthropic, Google and Meta have signed a letter asking the government to regulate the pace of AI development. The signatories argued that individual labs cannot slow development on their own.
Sarah Myers West of the AI Now Institute said human-in-the-loop systems can place responsibility on reviewers who have little context and little time to evaluate an AI system. She compared that risk with content moderation, where overworked staff can absorb blame for automated decisions.
Jain left Google after the company did not support the work he wanted to pursue. Bloomberg reported that the broader question is whether AI companies will give safety reviewers the working conditions and authority needed to challenge the systems they oversee.
Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our Editorial Policy.
