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Anthropic (ANTHROPIC) currently has a market cap of approximately $0.

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*Data last updated: 2026-04-16 05:18 (UTC+8)

As of 2026-04-16 05:18, Anthropic (ANTHROPIC) is priced at $0, with a total market cap of --, a P/E ratio of 0,00, and a dividend yield of %0,00. Today, the stock price fluctuated between $0 and $0. The current price is %0,00 above the day's low and %0,00 below the day's high, with a trading volume of --. Over the past 52 weeks, ANTHROPIC has traded between $0 to $0, and the current price is %0,00 away from the 52-week high.

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Learn More about Anthropic (ANTHROPIC)

Gate Learn Articles

Anthropic "Cuts Off" Windsurf, AI Coding Becomes "Proxy War" Among AI Giants

OpenAI's acquisition of the AI programming platform Windsurf has caused a stir in the industry, while Anthropic's cessation of the Claude model supply to Windsurf has further intensified market competition.

2025-06-11

Seventy-Two Hours of Anthropic’s Identity Crisis

In just seventy-two hours, Anthropic confronted a Pentagon ultimatum, public allegations from Elon Musk, and the withdrawal of its own safety pledges. From refusing to develop autonomous military weapons to revising RSP 3.0 and abandoning the "pause training" red line, this company—positioned as a leader in "safe AI"—is now grappling with a widening gap between its brand and operational reality. This article dissects the political dynamics, valuation pressures, and the unraveling of the safety narrative premium driving this identity crisis.

2026-03-05

Claude Code Source Code Leak: In-Depth Industry Analysis—Anthropic's Vision Extends Far Beyond Just an AI Coding Assistant

The Claude Code source code leak incident highlights more than a simple engineering error—it offers an early preview of Anthropic’s product strategy: background operations, automated execution, multi-agent collaboration, and permission automation. This article examines, from an industry standpoint, the probable directions Anthropic may pursue with Claude Code.

2026-04-02

Blogs

How many AI large language models has GateRouter integrated? Latest data as of April 2026

As of April 7, 2026, GateRouter has officially integrated with over 20 leading AI models, covering top global AI providers such as OpenAI, Anthropic, Google, xAI, and DeepSeek.

2026-04-07

Unraveling the Ethics and Sovereignty Debate in AI: Industry Insights Behind Anthropic’s Refusal of the Department of Defense

Anthropic, the AI company, chose to walk away from a $200 million contract rather than allow the US Department of Defense unrestricted access to its models. This article offers an in-depth breakdown of the timeline, core controversies, Silicon Valley’s stance, and the broader industry impact. We also explore the evolving landscape of AI ethics and sovereignty, examining how this

2026-02-28

FTX bankruptcy Claims Rise in OTC Markets, Estate Recovers $7.3 Billion

The value of FTX bankruptcy claims increase as the exchange recovers assets worth more than $7.3 billion.

2023-10-10

Anthropic (ANTHROPIC) FAQ

What's the stock price of Anthropic (ANTHROPIC) today?

Anthropic (ANTHROPIC) is currently trading at $0, with a 24h change of %0,00. The 52-week trading range is $0–$0.

What are the 52-week high and low prices for Anthropic (ANTHROPIC)?

What is the price-to-earnings (P/E) ratio of Anthropic (ANTHROPIC)? What does it indicate?

What is the market cap of Anthropic (ANTHROPIC)?

What is the most recent quarterly earnings per share (EPS) for Anthropic (ANTHROPIC)?

Should you buy or sell Anthropic (ANTHROPIC) now?

What factors can affect the stock price of Anthropic (ANTHROPIC)?

How to buy Anthropic (ANTHROPIC) stock?

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Anthropic (ANTHROPIC) Latest News

2026-04-16 04:31

OpenAI, Anthropic, and Google Team Up to Combat AI Model Distillation by Chinese Competitors

Gate News message, April 16 — OpenAI, Anthropic, and Google (Alphabet subsidiary) have begun collaborating to counter Chinese competitors' efforts to extract outputs from U.S. frontier AI models to enhance their own capabilities, according to Bloomberg. The three companies are sharing information through the Frontier Model Forum, a non-profit industry organization co-founded by OpenAI, Anthropic, Google, and Microsoft in 2023. The initiative aims to identify adversarial data distillation attempts that violate service terms. Data distillation refers to techniques used to replicate the performance of advanced AI models by analyzing their outputs, allowing competitors to develop comparable systems without direct access to proprietary technology.

2026-04-15 07:17

Anthropic Introduces Identity Verification for Claude to Prevent Abuse and Ensure Compliance

Gate News message, April 15 — Anthropic has rolled out an identity verification mechanism for certain use cases of Claude, aimed at preventing abuse, enforcing usage policies, and fulfilling legal obligations. The process is powered by Persona and requires users to submit a government-issued photo ID, with possible live selfie verification. Anthropic stated that verification data is used solely to confirm identity and will not be used for model training, marketing, or advertising. Users who fail verification can retry multiple times within the process or submit a form for manual assistance. Accounts may be suspended for repeatedly violating usage policies or terms of service, registering from unsupported regions, or being under 18 years of age.

2026-04-15 03:51

Anthropic Opposes Illinois AI Liability Bill Backed by OpenAI

Gate News message, April 15 — Anthropic is opposing Illinois bill SB 3444, which is backed by OpenAI. The bill would shield AI labs from liability for large-scale harm caused by misuse of their models, provided they draft and publish their own safety frameworks. Sources familiar with the matter said Anthropic has urged state senator Bill Cunningham and other lawmakers to change or drop the bill. Governor JB Pritzker's office stated he does not support giving big tech a full shield from responsibility. OpenAI said the measure would reduce risk and support a harmonized approach to state AI rules. Critics, including Thomas Woodside of Secure AI Project, argued the bill could nearly eliminate existing common law liability. Anthropic last week supported a separate Illinois bill that would require public safety plans and third-party audits for frontier AI developers.

2026-04-14 23:15

Cloud Startup Fluidstack in Talks to Raise $1B at $18B Valuation

Gate News message, April 14 — Fluidstack, a New York-based cloud infrastructure startup, is in talks to raise approximately $1 billion at a target valuation of $18 billion, according to people familiar with the matter. Jane Street and Situational Awareness are discussing co-leading the round, with Morgan Stanley serving as advisor. The company was valued at about $7.5 billion in an earlier funding round this year that included Situational Awareness. Fluidstack recently announced a $50 billion deal with Anthropic to build custom data centers. Fluidstack is a "neocloud" provider that supplies large clusters of GPUs to customers and works with partners to build dedicated computing capacity. Its expansion relies on former Bitcoin miners such as TeraWulf and Cipher Mining, which are converting power-intensive industrial sites into data centers. Google, an investor in Anthropic, has taken stakes in TeraWulf and Cipher. The $50 billion Anthropic deal signals a shift as AI firms move from renting standard cloud capacity to ordering custom-built infrastructure. This trend provides Bitcoin miners with a new revenue stream, helping them emerge from a profitability crisis by offering land and power for high-performance computing data centers. Cipher Mining and TeraWulf are pursuing long-term contracts for AI and HPC infrastructure to secure steadier cash flow than Bitcoin mining alone.

2026-04-14 06:01

Anthropic hires lobbying firm Ballard Partners, after talks with the Pentagon fell apart over AI use restrictions

Gate News message, on April 14, Anthropic has hired a lobbying firm, Ballard Partners, that is closely connected to the Trump administration. Relevant disclosure filings show that the cooperation took effect on March 9, a timing close to when the Pentagon issued its supply-chain risk determination for it. Reports say the core disagreement between the two parties in earlier negotiations falling apart was the scope of AI use. The Pentagon demanded unrestricted use of its tools, while Anthropic demanded that its products not be used for fully autonomous weapons deployment or large-scale surveillance targeting U.S. citizens. In addition, Ballard Partners is the sixth lobbying firm that Anthropic has hired since November 2024. Data shows that its 2025 federal lobbying spending increased year over year by more than 330% to about $3.1 million, reflecting a continued rise in policy-communication spending across the AI industry.

Hot Posts About Anthropic (ANTHROPIC)

Lifelike

35 minutes ago

OpenAI, Anthropic, and Google are collaborating to counter Chinese competitors' efforts to enhance AI capabilities by extracting outputs from U.S. models, and sharing information through the "Frontier Model Forum" to address adversarial data distillation.

GateNews

47 minutes ago

MarsBitNews

52 minutes ago

Title: How Anthropic Learned Mythos Was Too Dangerous for the Wild Author: Margi Murphy, Jake Bleiberg, and Patrick Howell O'Neill, Bloomberg Translation: Peggy, BlockBeats Author: BlockBeats Source: Reprint: Mars Finance Editor's note: When an AI company chooses not to release its most powerful model directly to the public, it already signals a problem. Anthropic's Mythos can now independently carry out a complete attack process. From discovering zero-day vulnerabilities, writing exploit code, to chaining multiple steps to access core systems—these tasks that once required top hackers working collaboratively over long periods have been compressed into hours or even minutes. This is why, immediately after disclosing the model, Scott Bessent and Jerome Powell convened Wall Street institutions to "self-check" using it. As the ability to find vulnerabilities is widely released, the financial system faces not scattered attacks but continuous scanning. Deeper changes lie in the supply structure. In the past, vulnerability discovery depended on a few security teams and hacker experience, with slow, non-reproducible rhythms. Now, this capability is beginning to be mass-produced by models, lowering the barriers for both attack and defense. An insider's analogy is straightforward: giving the model to an ordinary hacker is equivalent to equipping them with special operations capabilities. Institutions have already started using the same tools to perform reverse checks on their own systems. JPMorgan Chase, Cisco Systems, and others are testing internally, hoping to patch vulnerabilities before they are exploited. But the reality remains unchanged: discovery speeds are increasing, but fixing remains slow. "We’re good at finding vulnerabilities, but not at fixing them," said Jim Zemlin, highlighting the mismatch in pace. In fact, Mythos is not just an incremental improvement in single-point capabilities but an integration, acceleration, and lowering of the barriers to previously scattered and limited attack abilities. Once outside controlled environments, how this capability will spread remains an uncharted territory. The danger is not what it can do, but who can use it and under what conditions. Below is the original text: On a warm evening in February, during a wedding in Bali, Nicholas Carlini temporarily stepped away, opened his laptop, and prepared to "cause some trouble." At that moment, Anthropic had just opened a new AI model called Mythos for internal testing, and this renowned AI researcher was about to see how much trouble it could stir up. Anthropic hired Carlini to "stress test" their AI models, assessing whether hackers could use them for espionage, theft, or sabotage. During the Bali wedding, Carlini was shocked by the model’s capabilities. Within a few hours, he found multiple techniques usable for infiltrating widely used global systems. When he returned to Anthropic’s office in downtown San Francisco, he discovered that Mythos could autonomously generate powerful intrusion tools, including attack methods targeting Linux—one of the backbone open-source systems supporting modern computing. Mythos staged a "digital bank heist": it could bypass security protocols, enter networks through the front door, and then crack digital vaults to access online assets. Previously, AI could only "pick locks," but now it has the ability to plan and execute entire "robberies." Carlini and some colleagues began alerting the company about their findings. Meanwhile, they were discovering high-risk and even deadly vulnerabilities in systems Mythos probed—issues usually only top global hackers could uncover. At the same time, an internal team called "Frontier Red Team"—comprising 15 members, known as "Ants"—was conducting similar tests. Their role was to ensure the company's models wouldn’t be used to harm humanity. They tested with robotic dogs in warehouses, collaborating with engineers to see if chatbots could maliciously control these devices; they also worked with biologists to assess whether models could be used to create biological weapons. This time, they gradually realized that the greatest risk Mythos posed came from cybersecurity. "Within hours of getting the model, we knew it was different," said Logan Graham, who led the team. Previous models like Opus 4.6 had already shown the ability to assist humans in exploiting software vulnerabilities. But Graham pointed out that Mythos could "act on its own" to exploit these vulnerabilities, posing a national security risk. He warned senior management, facing a tough dilemma: explaining that the company's next major revenue engine might be too dangerous for public release. Anthropic co-founder and Chief Scientist Jared Kaplan said he had been "closely monitoring" Mythos during its training. By January, he realized the model’s extraordinary ability to discover system vulnerabilities. As a theoretical physicist, Kaplan needed to determine whether these abilities were just "technically interesting phenomena" or "a real problem highly related to internet infrastructure." His conclusion was the latter. In late February to early March, Kaplan and co-founder Sam McCandlish debated whether to release the model. In the first week of March, top executives—including CEO Dario Amodei, President Daniela Amodei, and Chief Information Security Officer Vitaly Gudenets—met to hear Kaplan and McCandlish’s reports. They concluded that Mythos’s risks were too high for full public release, but some companies, even competitors, should be allowed to test it. "We quickly realized this had to be a very different approach; it wouldn’t be a routine product launch," Kaplan said. By the first week of March, the company finally agreed to deploy Mythos as a cybersecurity defense tool. Market reactions were almost immediate. On the day Anthropic disclosed Mythos’s existence, U.S. Treasury Secretary Scott Bessent and Federal Reserve Chair Jerome Powell convened an emergency meeting with major Wall Street firms in Washington. The message was clear: use Mythos immediately to identify vulnerabilities in your systems. Sources close to the meeting (who requested anonymity due to private discussions) revealed the seriousness—participants even refused to disclose details to some core advisors. The White House issued an urgent warning about Mythos’s potential as a hacking tool and recommended "using it for defense," signaling a deeper shift: AI is rapidly becoming a decisive force in cybersecurity. Anthropic has limited Mythos’s access in "Project Glasswing" to select organizations, including Amazon Web Services, Apple, and JPMorgan Chase, for testing; government agencies have also shown strong interest. Before public release, Anthropic fully briefed U.S. officials on Mythos’s capabilities, including its potential for cyberattacks and defenses. The company is also in ongoing discussions with multiple governments. An anonymous employee involved in internal affairs disclosed this. Competitor OpenAI quickly followed, announcing on Tuesday a tool called GPT-5.4-Cyber for discovering software vulnerabilities. Early tests of this version revealed dozens of "concerning" behaviors, including ignoring human instructions and, in rare cases, attempting to conceal actions after violating commands. Currently, Mythos has not been officially released as a cybersecurity tool, and external researchers have yet to fully verify its capabilities. However, the company's rare decision to restrict access reflects a growing industry and government consensus: AI is reshaping the cybersecurity economy—significantly lowering the cost of discovering vulnerabilities, compressing attack preparation time, and reducing technical barriers for certain attack types. Anthropic also warns that Mythos’s increased autonomous action capability itself poses risks. During testing, the team observed unsettling cases: models disobeyed instructions or tried to cover their tracks after violations. In one incident, the model designed a multi-step attack chain, "escaping" a restricted environment, gaining broader internet access, and actively publishing content. In the real world, complex and hidden code vulnerabilities in banking and hospital systems often take weeks or months for professionals to find. Once hackers exploit these vulnerabilities first, it can lead to data leaks or ransomware attacks with severe consequences. However, many influential figures question Mythos’s true capabilities and potential risks. White House AI advisor David Sacks posted on X: "More and more people are doubting whether Anthropic is the 'boy who cried wolf' in AI. If the threats Mythos poses don’t materialize, the company will face serious credibility issues." The reality is that hackers have already begun using large language models for complex attacks. For example, a cyber espionage group used Anthropic’s Claude to attempt infiltrating about 30 targets; others have used AI to steal data from government agencies, deploy ransomware, and rapidly breach hundreds of firewalls designed for data protection. An insider revealed that U.S. national security officials see Mythos’s emergence as creating unprecedented uncertainty—assessing cybersecurity risks has become more difficult. Giving this model to individual hackers is akin to elevating an ordinary soldier directly into special forces. Meanwhile, such models could become "capability amplifiers": enabling a criminal hacker group to possess attack power comparable to a small nation, or allowing mid-sized countries’ intelligence and military hackers to execute cyberattacks once thought only possible by major powers. Former NSA Cybersecurity Chief Rob Joyce said: "I do believe that, in the long run, AI will make us safer and more secure. But between now and some future point, there will be a 'dark age'—a period when offensive AI has a clear advantage, and those without solid defenses will be the first to be compromised." Notably, Mythos is not the only model with such capabilities. Early versions of Claude and Big Sleep are also used by various organizations for vulnerability discovery. An insider explained that "zero-day" vulnerabilities—those unknown to defenders—once took days or weeks to identify and exploit; now, AI can do it in an hour or even minutes. Zero-day refers to security flaws that defenders haven't yet detected, leaving little time for patching. Currently, JPMorgan Chase is focusing on supply chain and open-source software vulnerabilities, having already discovered multiple issues and reported them to vendors. CEO Jamie Dimon said during earnings calls that Mythos "indicates there are still many vulnerabilities to fix." An anonymous source said JPMorgan Chase had already discussed testing Mythos before it was publicly known, but declined to comment further. Other Wall Street banks and tech firms are also trying to use Mythos to patch vulnerabilities before hackers find them. According to Bloomberg, Goldman Sachs, Citigroup, Bank of America, and Morgan Stanley are all testing internally. Cisco’s security chief Anthony Grieco is especially concerned about whether attackers might use AI to find exploits in their global network devices—routers, firewalls, modems. He worries AI could accelerate attacks on "end-of-life" devices that will no longer receive updates from Cisco. Fixing vulnerabilities discovered by AI remains a long-term challenge. This process, called "security patching," is often costly and lengthy, leading many organizations to ignore known issues. The catastrophic breach at Equifax, where data of 147 million people was stolen, was caused by unpatched vulnerabilities. Despite refusing to assist in mass surveillance of U.S. citizens, Anthropic was labeled a "supply chain threat" by the Trump administration, but the company continues to engage with federal agencies. The U.S. Treasury is seeking access to Mythos this week. Treasury Secretary Scott Bessent said the model will help the U.S. maintain an edge in AI. In a test, Mythos generated browser attack code chaining four different vulnerabilities into a complete exploit chain—an extremely challenging task even for human hackers. Cybersecurity reports note that such "vulnerability chains" can breach highly secure systems, similar to how Stuxnet targeted Iranian nuclear centrifuges. Additionally, Anthropic states that, when explicitly instructed, Mythos can even identify and exploit zero-day vulnerabilities in all major browsers. They also used Mythos to find vulnerabilities in Linux code. Jim Zemlin pointed out that Linux "supports most of today’s computing systems," from Android smartphones and internet routers to NASA supercomputers—almost everywhere. Mythos can autonomously find flaws in open-source code, and once exploited, attackers could take full control of machines. Currently, the Linux Foundation has dozens of personnel testing Mythos. Zemlin sees a key issue: whether Anthropic’s model can provide valuable insights to help developers write safer software from the source, reducing vulnerabilities. "We’re good at finding vulnerabilities," he said, "but we’re terrible at fixing them."

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