Tom Lee Still Predicts ETH Will Reach $250,000. Do You Still Believe?

Foresight NewsPublished on 2026-06-06Last updated on 2026-06-06

Abstract

Tom Lee, Chairman of Bitmine and Head of Research at Fundstrat, predicts Ethereum (ETH) could reach $250,000, driven by AI and tokenization transforming financial infrastructure. Speaking at the Paris Proof of Talk conference, he argued that a machine-to-machine economy will require fast, blockchain-based payments, positioning ETH as a primary global currency for automated computation. Lee highlighted Bitmine's recent purchase of 111,942 ETH, bringing its holdings to nearly 5.4 million ETH, or about 4.47% of circulating supply. He noted the Ethereum Foundation's declining influence (now holding only 0.1% of supply) is being replaced by corporate validators like Bitmine, which generate significant staking rewards. Lee also announced Bitmine qualifies for inclusion in the Russell 1000 index, seeing its staking model as superior to holding spot ETH. He views current bearish sentiment as a market bottom for both Bitcoin and Ethereum.


Author: Olivier Acuna

Compiled by: AididiaoJP


Bitmine Chairman Tom Lee has made his boldest ETH prediction to date: first to $5,000, then a 50x gain. (Image: Olivier Acuna / CoinDesk)


Key Points


  • Tom Lee, Head of Research at Fundstrat and Chairman of Bitmine, stated at a conference in Paris that Ethereum could ultimately reach $250,000 as AI and tokenization drive a major shift in financial infrastructure.
  • Bitmine recently purchased 111,942 ETH, increasing its holdings to nearly 5.4 million ETH, representing about 4.47% of the circulating supply. Lee believes corporate validators will replace the shrinking Ethereum Foundation as the primary stewards of the network.
  • Lee stated that Bitmine now qualifies for inclusion in the Russell 1000 index and argued that its staking-focused model is far superior to directly holding spot ETH. He believes the current bearish sentiment signals a market bottom for both Bitcoin and Ethereum.


The cryptocurrency market is focused on the wrong signals, while a massive shift in how the global financial network operates is quietly taking place.


In a keynote speech at the Proof of Talk conference in Paris, Tom Lee, Head of Research at Fundstrat and Chairman of Bitmine Immersion Technologies (BMNR), told the audience that Ethereum (ETH) is undergoing a significant transformation that will ultimately drive its price to $250,000. While Lee did not provide a specific timeline, he elaborated on the infrastructural shifts propelling the network towards this valuation.


On Tuesday, Ethereum's price fluctuated around $1,906, down 6% in 24 hours.


Lee's Bitmine is one of the largest corporate holders of Ethereum. The company intensified its ETH purchases last week, completing its largest buy of the year—acquiring 111,942 ETH (worth approximately $237 million at current prices). This move increased its holdings to nearly 5.4 million ETH, representing about 4.47% of Ethereum's circulating supply.


"If the thesis is correct, Ethereum is about to break out of consolidation, and the catalyst for this breakout is tokenization and AI, then I think there's about a 50x upside—a significant rally for Ethereum. If ETH achieves that, reaching $250,000, then Bitmine stock would be worth $5,000. At $18, it's an absolute steal right now."


Trillions in Growth


Lee explained that this multi-trillion dollar growth will be driven by artificial intelligence. As advanced software and automated computing take over the internet, machines will need a method for instant payments without relying on slow traditional bank transfers.


"Robots are already about to dominate most of the traffic on the internet," Lee said. "That's why firms like Andreessen Horowitz call it the 'Great Unification.' If you have robotic systems, you must control them. And blockchain is much more effective at controlling robot behavior than traditional systems. Whether it's authentication, identification, or payment speed, all of these work better on a crypto system."


Due to this machine-to-machine economy, Lee believes Ethereum will transform from a speculative digital asset into the primary global currency for paying for automated computing power.


The Ethereum Foundation Loses Its Voice


This systemic growth is fundamentally changing the governance of the underlying blockchain network. Lee pointed out that the non-profit Ethereum Foundation has been scaling down its footprint for years, with its network holdings reduced to just 100,000 ETH—only 0.1% of the total supply.


Instead, major public companies are entering as corporate validators to operate the network. Corporate entities like Bitmine and Sharplink now collectively control about 7% of Ethereum's circulating supply. These corporate treasuries, no longer reliant on foundation grants, generate roughly $500 million in annual staking rewards to self-fund the ecosystem.


To showcase the value of this model, Lee announced a major regulatory milestone for Bitmine—the company trades on the NYSE under the ticker BMNR.


"Bitmine also qualifies for inclusion in the Russell 1000 index," Lee revealed. "The inclusion date is June 26th. Why is this important? The Russell 1000 is the most widely tracked index globally... All portfolio managers globally benchmarked to the Russell 1000—totaling over $4 trillion—will have to decide whether to hold Bitmine."


Using presentation charts, Lee explained that holding shares of active corporate validators significantly outperforms buying spot cryptocurrency directly. Over a benchmark six-month period, holding plain spot ETH returned 22%, while Bitmine's staking architecture delivered a 500% return for investors.


In Lee's view, the massive structural growth from corporate staking and AI utility completely overshadows any temporary market fears. "If you're bearish today, you're selling at the bottom," Lee concluded. "Let me say it again, if you're bearish on Bitcoin and Ethereum today, you're bearish at the bottom."

Related Questions

QWhat is the key factor driving Tom Lee's prediction of Ethereum reaching $250,000?

ATom Lee believes the primary factor driving Ethereum's potential to reach $250,000 is a major transformation in financial infrastructure propelled by Artificial Intelligence (AI) and tokenization, where Ethereum will become a primary currency for automated, machine-to-machine payments.

QWhat recent action did Bitmine take regarding its ETH holdings, and what is its current stake in the Ethereum network?

ABitmine recently purchased 111,942 ETH, bringing its total holdings to nearly 5.4 million ETH. This represents approximately 4.47% of Ethereum's circulating supply.

QAccording to Tom Lee, what is a significant milestone for Bitmine (BMNR) and why is it important?

AA significant milestone for Bitmine is that it has qualified for inclusion in the Russell 1000 Index. This is important because the Russell 1000 is a widely tracked index, and fund managers globally who benchmark against it (representing over $4 trillion in assets) must decide whether to hold Bitmine stock.

QHow does Tom Lee describe the changing governance of the Ethereum network and the role of the Ethereum Foundation?

ATom Lee describes a shift where the non-profit Ethereum Foundation is gradually losing influence as its holdings have shrunk to about 100,000 ETH (0.1% of supply). He states that large public companies like Bitmine and Sharplink, acting as corporate validators, are becoming the primary stewards of the network.

QWhat advantage does Tom Lee claim Bitmine's staking model has over simply holding spot ETH?

ATom Lee claims that Bitmine's staking architecture for investors has significantly outperformed holding spot ETH. He presents data showing a 500% return for Bitmine's model over a six-month benchmark period, compared to a 22% return for holding spot ETH.

Related Reads

It Took Me a Year to See the Hard Truth About Agent Payments

**Title: It Took Me a Year to See the Hard Truth About Agent Payments** Over the past year, I've worked on infrastructure for the Agent economy, engaging with major players like Stripe, Visa, Coinbase, and numerous startups. The findings reveal a stark reality: genuine, widespread demand for Agent-based payments does not yet exist. **Key Observations:** * **Agent-to-Merchant (Shopping):** The user experience for AI shopping often falls short, especially for visual product discovery. While AI excels at understanding needs, conversational interfaces can't yet replace browsing and comparing multiple products visually. Current merchant interest is largely defensive ("Agent Engine Optimization") for a future that hasn't arrived. High-frequency, low-friction purchases (like food delivery) are potential fits, but lack open APIs and face high AI inference costs. Simpler, more affordable, or cross-language interactions for complex UIs are a niche opportunity but require massive consumer distribution to scale. * **Agent-to-API (Developer Tools):** Developer payment needs for APIs (computing, data, models) are already met through subscriptions and prepaid credits. The core challenge is not payment friction but supplier economics: most large SaaS providers prefer enterprise contracts over micropayments for API calls. Protocols like MPP and x402 suit the long-tail of smaller services but cater to a developer market historically reluctant to pay for these tools. Major infrastructure needs at the top of the stack are already being addressed. * **Agent-to-Agent (Machine Commerce):** This is a long-term vision with almost no current transaction volume. While a future with high-speed, high-frequency, multi-party machine-to-machine transactions would require novel infrastructure, it remains theoretical. The market is not here yet. * **Agent-to-Finance:** This is the only category with clear, present demand. Financial professionals and DeFi users already pay for tools, and AI augmentation is a natural evolution. Autonomous AI agents can enable entirely new financial strategies. However, competition is fierce from established, regulated incumbents who can more easily layer AI onto their existing products. **The Core Insight:** Companies, especially giants with long time horizons, are building defensively for a potential future of mass machine commerce. For them, early investment is a low-cost hedge. For startups, the current market reality is different. The primary challenge isn't just moving money between agents (payments). The larger, unsolved problem is **orchestration** – coordinating work between agents and humans, verifying outcomes, and then settling. Payment is just a part of settlement, which is just a part of orchestration. Companies that solve the orchestration problem will subsume payments, not the other way around. After a year of building, we see the real, growing, and underserved market opportunity lies in this broader domain of orchestration.

链捕手23m ago

It Took Me a Year to See the Hard Truth About Agent Payments

链捕手23m ago

Claude Opus 4.8 Finds a $4.5 Billion Bug: The AI Era is Mass-Producing Hackers

A researcher discovered a critical "infinite mint" vulnerability in the Zcash cryptocurrency's Orchard protocol using Claude Opus 4.8, leading to a swift fix but also a 50% market drop, erasing billions in value. This incident highlights a new era where powerful, accessible AI models are dramatically lowering the barrier to finding software vulnerabilities. Previously, the security community feared specialized models like Claude Mythos Preview, capable of finding decades-old zero-day exploits. The Zcash case, however, involved a publicly available, general-purpose model. This shift makes advanced security auditing—and attack capabilities—accessible to far more people, not just experts. The mass democratization of vulnerability discovery brings a dual challenge: a flood of low-quality, AI-generated false reports that overwhelm maintainers, and the real, rapid uncovering of deep, dangerous bugs. Open-source projects, often understaffed and unfunded, are particularly vulnerable to this "attention DDoS." The article cites examples like curl shutting down its bug bounty program due to the unsustainable workload. Our perceived digital safety has often been luck, relying on the high cost and effort required to find deeply hidden flaws in complex systems, as seen with historical vulnerabilities like Heartbleed or Baron Samedit. AI changes this cost structure, effectively "mass-producing flashlights" to illuminate every corner of our codebase. While large companies operate extensive security chains involving external white-hat hackers and massive defensive operations, the global cybersecurity workforce faces a severe shortage, especially of experienced personnel capable of analyzing complex threats and coordinating fixes. The core dilemma emerges: AI makes *finding* bugs cheap and scalable, but *fixing* them remains a slow, expensive, and human-intensive process. The article concludes that AI won't destroy the internet but acts as a bright light, revealing that our digital existence is not inherently secure but is precariously maintained by ongoing human effort. The true cost in the AI era may not be discovery, but whether there will be enough people left willing and able to do the hard work of repair.

marsbit56m ago

Claude Opus 4.8 Finds a $4.5 Billion Bug: The AI Era is Mass-Producing Hackers

marsbit56m ago

Codex Goal Mode Usage Guide: How to Make AI Continuously Pursue a Specific Objective

"Codex Goal Mode: How to Make AI Work Continuously Toward a Specific Goal" OpenAI's Codex "goal mode" (/goal) transforms the AI from a reactive code assistant into a proactive execution agent capable of working autonomously for hours or even days to achieve a defined objective. To maximize its effectiveness, follow these key principles: 1. **Define Clear, Verifiable Exit Criteria:** The goal prompt should be a concise, measurable success condition, not a lengthy specification. Use quantifiable metrics like "reduce build time by 30%" or "achieve 100% test parity." 2. **Provide Initial Guidance and Tools:** Direct Codex toward likely problem areas and specify available tools (e.g., browsers, testing environments) to prevent it from exploring unproductive paths. 3. **Enable Progress Measurement:** Equip Codex with ways to track advancement, such as creating comparison tools for visual tasks or evaluation sets, ensuring it can gauge its own progress. 4. **Use a Realistic Execution Environment:** For tasks like performance optimization, provide access to environments that closely mimic production (e.g., similar configs, databases) to yield valid results. 5. **Be Cautious with Visual Goals:** Avoid vague "pixel-perfect" instructions. Instead, supplement visual references with functional checklists or design system specifications to prevent Codex from obsessing over minor details. 6. **Implement Progress Tracking:** For long-running tasks, have Codex commit code to draft PRs, update progress documents, or send Slack updates to maintain visibility into its work. 7. **Review and Consolidate Results:** Once the goal is met, instruct Codex to review its work, clean up ineffective experimental code, and reflect on what strategies succeeded or failed. Ultimately, using goal mode shifts the developer's role from writing prompts to managing a persistent engineering agent—defining objectives, establishing metrics, configuring environments, and conducting final reviews.

marsbit2h ago

Codex Goal Mode Usage Guide: How to Make AI Continuously Pursue a Specific Objective

marsbit2h ago

From Ethereum to AI's 'CROPS': What Exactly Is This 'Slow Variable' That Vitalik Has Repeatedly Emphasized?

Recently, Vitalik Buterin has frequently emphasized the concept of "CROPS," first outlined in the Ethereum Foundation's March mandate as core principles guiding its focus: Censorship Resistance, Capture Resistance, Open Source, Privacy, and Security. CROPS represents Ethereum's commitment to providing foundational capabilities for user sovereignty—enabling asset ownership, identity expression, and coordination without reliance on centralized platforms or surrendering ultimate control. This framework is gaining new urgency with the rise of AI, particularly AI agents managing digital assets and automating transactions. While AI offers convenience, it risks centralizing user data, intent, and control if dependent on opaque, centralized services. Vitalik argues for "CROPS AI"—AI that is open, privacy-preserving, secure, and capable of local execution to maintain user agency. He highlights convergence between "CROPS Ethereum access layers" and "CROPS AI," such as using zero-knowledge proofs for private remote LLM calls and Ethereum RPC reads, ensuring users can access services without exposing sensitive information. Ultimately, CROPS is not just an abstract ideal but a practical guide for Ethereum's development and AI integration. It addresses the critical long-term question: as digital systems grow more powerful, how can users retain control over their privacy, assets, and autonomy? In an AI-driven era, these principles may define Ethereum's enduring value—prioritizing verifiable, secure, and user-centric design over short-term optimizations like speed and cost alone.

marsbit2h ago

From Ethereum to AI's 'CROPS': What Exactly Is This 'Slow Variable' That Vitalik Has Repeatedly Emphasized?

marsbit2h ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of ETH (ETH) are presented below.

活动图片