$300 Billion in One Quarter, AI Absorbs 80% of Global Venture Capital Funding

marsbitPublished on 2026-04-03Last updated on 2026-04-03

Abstract

In Q1 2026, global venture capital funding reached a record $300 billion, with AI capturing 80% ($242 billion) of the total. Four mega-deals dominated: OpenAI ($122B), Anthropic ($30B), xAI ($20B), and Waymo ($16B), accounting for two-thirds of the quarter’s funding. The market showed extreme concentration, with fewer deals and larger average rounds, indicating a fragile breadth beneath the headline numbers. Crypto funding saw a modest recovery, reaching approximately $8.6 billion, though two-thirds of this occurred in March. Capital flowed mainly into regulated infrastructure like stablecoin payments, custody, and compliance, rather than speculative projects. Broader trends included growth in robotics, defense tech, and cybersecurity—often adjacent to AI. Geographically, the U.S. dominated with 83% of total funding, followed by China and the U.K. The venture market is increasingly fragmented: U.S.-led AI platforms attract massive late-stage capital, China’s on state-driven funding, and Europe faces a growth capital gap. Looking ahead, VC totals may remain high but concentrated. Valuation discipline is returning in secondary markets, exit windows remain volatile, and crypto must compete with AI for investor attention. The market is defined by selectivity and divergence, not broad recovery.

Author: insights4vc

Compiled by: Deep Tide TechFlow

Deep Tide Guide: insights4vc reviews the global venture capital market in Q1 2026. This quarter saw total funding of approximately $300 billion, hitting a new historical high, but 80% flowed into AI. OpenAI alone raised $122 billion, Anthropic $30 billion, xAI $20 billion, and Waymo $16 billion—these four deals accounted for two-thirds of global venture capital. Crypto funding saw a slight recovery, with about $8.6 billion in Q1, but two-thirds of that was concentrated in March, and funds primarily went to stablecoin payments and compliance infrastructure, while speculative projects remained cold.

Main Text:

The venture capital market in 2026 has entered a new phase. It no longer resembles a broad financing market supporting startups but functions more like a late-stage capital allocation machine revolving around a few AI platforms. Behind the record-breaking numbers lie extreme concentration at the top, fragile market breadth, and a still highly selective crypto recovery.

Caption: Global VC funding in Q1 2026 (Source: crunchbase.com)

Core Summary

  • Global VC funding in Q1 2026 was approximately $300 billion, covering about 6,000 companies, setting a new quarterly record. Late-stage and tech growth rounds contributed the majority of the funds.
  • AI captured the vast majority of capital: Crunchbase estimates about $242 billion, accounting for 80% of the quarter's total, a significant increase from AI's share a year ago.
  • The market exhibits a barbell structure: a few global strategic platforms received unprecedented funding pools, while broader deal volume remains sluggish, and fundraising conditions for most funds are still challenging.
  • Crypto and digital assets improved compared to the trough, but the rebound is narrow and highly dependent on timing. In some data sources, the explosive growth in March explains most of the crypto VC funding in Q1.
  • Within the crypto space, capital continues to migrate towards regulated channels and utility infrastructure (stablecoin payments, custody, compliance, tokenization), aligning with the increasingly clear policy environments in the U.S. and EU.
  • Areas still receiving funding outside of AI include robotics (often with AI attributes), defense tech, cybersecurity, and some fintech, but their importance is increasingly reflected through "AI adjacency" and sovereign/corporate strategic logic.

Q1 Data Overview

Crunchbase data shows global VC funding in Q1 2026 was approximately $300 billion, covering about 6,000 startups, with both quarter-on-quarter and year-on-year growth exceeding 150%. This figure is close to 70% of the total VC funding for the entire year of 2025.

However, the record amount does not imply record breadth. By stage, late-stage funding was about $246.6 billion across 584 deals; early-stage about $41.3 billion across 1,800 deals; and seed stage about $12 billion across approximately 3,800 deals. Even at the seed stage, some data shows rising amounts but a significant year-on-year decline in the number of deals. In other words, the average round size has increased, but the deal surface has not expanded. Investors are concentrating their time and allocations on fewer targets.

A simple but useful distinction is to separate "total volume" from "total volume excluding outliers." Just four super-sized rounds accounted for a large portion of global VC funding in Q1. Removing these outliers, the remaining portion is roughly around $100 billion, similar to the "strong but not record-breaking" quarters of 2024-2025. Q1 2026 broke records mechanically due to its reliance on a handful of deals.

Geographically, U.S. companies raised about $250 billion, accounting for approximately 83% of global VC funding, further increasing from an already high share. The second-largest market was China, with about $16.1 billion, and the third was the UK, with about $7.4 billion. This aligns with the basic fact that frontier AI and compute investments are most easily realized in the U.S., due to the high density of hyperscale cloud providers, concentrated GPU supply chains, and investor willingness to fund multi-year infrastructure spending.

AI Dominated This Quarter

AI's dominance in Q1 2026 cannot be ignored. Crunchbase estimates AI-related companies raised approximately $242 billion, accounting for 80% of global VC funding. For comparison: in Q1 2025, AI funding was about $59.6 billion, representing 53% of that quarter's total. Even considering database backfilling and definition drift, the direction is clear: AI has gone from the largest vertical to, on a funding-weighted basis, the venture capital market itself.

Caption: Quarterly trend of global AI funding (Source: crunchbase.com)

What has changed is not just the degree of enthusiasm. The funding model itself is shifting towards infrastructure underwriting, with funding rounds for a few companies resembling capital market events more than traditional venture capital. Four of the five largest VC rounds in history were completed in Q1 2026: OpenAI ($122 billion), Anthropic ($30 billion), xAI ($20 billion), and autonomous driving company Waymo ($16 billion), totaling $188 billion and accounting for approximately 65% of global VC funding.

Caption: Anthropic - Coatue Forecast Model

Anthropic's valuation logic is also supported by exceptionally strong operational data. According to Reuters, around its February 2026 funding, Anthropic's total annualized revenue had reached approximately $14 billion, with its Claude Code product alone generating over $2.5 billion in annualized revenue, and enterprise subscriptions quadrupling in 2026. By early March, Reuters reported total annualized revenue had further risen to about $19 billion. Investor enthusiasm stems not only from the option value of frontier models but also from rapidly materializing enterprise monetization capabilities. This explains why Anthropic is increasingly seen as a cleaner AI exposure, particularly in programming and enterprise workflow infrastructure.

Caption: Coatue forecasts Anthropic's valuation at $1.995 trillion by 2030

One deal epitomizes this paradigm shift. On March 31, OpenAI announced the completion of a $122 billion funding round at an $852 billion post-money valuation. The company explicitly positioned compute access as a core strategic bottleneck and outlined an infrastructure strategy spanning multiple cloud partners and chip platforms. The other two frontier labs reinforced the same model: Anthropic announced a $30 billion Series G in February at a $380 billion post-money valuation, with funds explicitly for frontier research, product development, and infrastructure expansion; xAI announced an expanded $20 billion Series E in January, with the core use also being large-scale compute infrastructure construction.

OpenAI's record-breaking funding also exposed an important market tension. Although it remains the largest capital magnet in AI, its shares are reportedly no longer sought after in the secondary market, with some institutional holders struggling to find buyers, while demand for Anthropic equity is strengthening. Bloomberg reported investors are shifting towards Anthropic, suggesting that scale alone may no longer be sufficient to sustain unlimited market demand for OpenAI at current price levels.

This is crucial because OpenAI's latest round's investor structure doesn't resemble a traditional VC syndicate. It was a strategic financing anchored by key suppliers and ecosystem partners, including Amazon, NVIDIA, SoftBank, and Microsoft, alongside over $3 billion raised from individual investors through banking channels. Effectively, this更像是 a mobilization of infrastructure-supportive balance sheets around a company deemed systemically important to the AI stack, rather than a pure expression of broad market confidence.

This distinction is important. It means frontier labs' primary market funding can maintain massive scale even as secondary market buyers become more valuation-sensitive. Anthropic raising $30 billion at a $380 billion post-money valuation reinforces this view: for many investors, Anthropic may offer a cleaner upside/price ratio compared to OpenAI at $852 billion. The broader implication is that late-stage AI capital is diverging—strategic capital is willing to support compute-intensive leaders at super scale, while financial capital is looking for the next relative winner, not the current category leader.

From this perspective, Q1 2026 is not only a record quarter for AI funding but also an early signal of valuation discipline beginning to re-enter the space through the secondary market, even as primary market round sizes continue to expand.

For institutional investors, a key细分 is that Q1 2026 AI funding should be broken into subcategories with varying durability: frontier model companies, infrastructure and data centers, chips and compute supply chain, agent and enterprise workflow platforms, robotics and autonomous systems, defense-related deployments. Most of this quarter's funding flowed to the most infrastructure-intensive layers, where competitive advantage is demonstrated through locked-in compute, distribution channels, and regulatory positioning, not just model quality.

Waymo is a典型案例 of the "physical AI" effect. The company raised $16 billion in February at a $126 billion post-money valuation, with funds explicitly for global expansion of autonomous mobility. Although often categorized under autonomous driving, Waymo's positioning and investment narrative increasingly fall under the broader "AI entering the physical world" category.

The resulting second-order effect is concentration risk. When four deals can account for two-thirds of global quarterly VC, record funding numbers are a fragile signal for startup health, job creation, and innovation breadth. For allocators: performance dispersion between top AI exposure and the rest of the VC ecosystem is more likely to widen than narrow.

Crypto's Position in the New VC Cycle

For specialized investors, crypto and digital assets were the second most relevant theme in Q1 2026, but the absolute scale is much smaller than AI. In crypto-specific funding trackers, Q1 2026 funding is typically in the high single-digit billions of dollars, with high monthly volatility. CryptoRank data shows 252 funding rounds in Q1, totaling $8.632 billion. March alone contributed approximately $5.95 billion (107 rounds), meaning about two-thirds of Q1 crypto VC funding occurred in the final month.

Caption: Crypto funding trends (Source: cryptorank.io)

This temporal concentration is the first reason for caution regarding a "rebound." A quarter pulled by a single month is susceptible to data revision risks (delayed reporting, reclassification) and narrative risks (a few deals being misinterpreted as a broad recovery). A second caution is the discrepancy among data providers. Other widely circulated crypto funding statistics for early 2026 show significant differences in amounts and deal counts due to varying scopes (venture equity vs. debt, PIPE, post-IPO financing, treasury financing strategies, acquisitions, undisclosed rounds).

Compared to historical cycles, Q1 2026 crypto VC更像是 a continuation of the "utility and channels" phase, not a broad speculative boom. In Q1 2025, CryptoRank estimated crypto VC funding at $4.8 billion, explicitly noting that a single $2 billion investment drove most of that quarter's data. Q1 2026 is similar—crypto remains highly sensitive to outliers, but the narrative focus has shifted from exchanges to stablecoin infrastructure and institutional enablement.

Specific cases support this "channels first" judgment. According to Reuters, stablecoin infrastructure company Rain raised a $250 million Series C at a $1.95 billion valuation, positioned for stablecoin-linked payment cards and wallets. Reuters also reported OpenFX raised $94 million to expand cross-border payment infrastructure based on stablecoins, with the product positioned for faster settlement and lower costs than traditional correspondent banking. These are not "token launch" stories but stories about payments and fund conduits with crypto underpinnings.

The macro and regulatory background also helps explain why stablecoins and tokenization continue to attract funding even amid crypto price volatility. KPMG's "Pulse of Fintech" report showed global total investment (including VC, PE, and M&A) in the "digital assets"领域 nearly doubled to $19.1 billion in 2025, explicitly citing driving factors: full implementation of EU MiCA, the U.S. GENIUS Act, and rising market interest in stablecoins and asset tokenization (particularly money market funds). The implication for Q1 2026 is: when crypto can integrate into regulated financial workflows (payments, custody, compliance, tokenized cash equivalents), the investor base broadens to include institutional capital previously absent.

But the rebound surface remains narrow. Even if Q1 2026 crypto VC reached $8-9 billion in some trackers, measured against the $300 billion global VC total, crypto's share remains in the low single digits. This creates an important strategic trade-off: crypto may marginally benefit from improved risk appetite, but it competes for attention with AI opportunities that have larger ticket sizes and faster adoption speeds.

A final detail is that crypto funding numbers might be distorted by large potential financings for mature giants, which may not translate into broad startup ecosystem funding. According to Reuters, Tether downplayed numbers around its potential multi-billion dollar funding discussions after reports of investor resistance emerged, suggesting that even if large deals happen, they reflect more about late-stage balance sheet strategies than ecosystem-wide early-stage expansion.

Broader Market Map

Beyond AI and crypto, Q1 2026 still offers signals about the positioning of the next VC cycle, but many are increasingly "AI-adjacent" rather than independent. Crunchbase data and commentary in late 2025 and early 2026 highlighted strong funding momentum in robotics, defense tech, cybersecurity, and some fintech, with common threads of automation, sovereignty, and infrastructure.

Robotics is a good case study. Crunchbase reported nearly $14 billion in robotics VC funding in 2025, up about 70% year-on-year, surpassing the 2021 peak. For institutional investors, this is not a "robotics hype" story but more a consequence of AI capital allocation: as models become commoditized, investors look for defensible moats in hardware integration, deployment constraints, and regulated operating environments.

Defense and dual-use technologies similarly sit at the intersection of geopolitics and AI capabilities. Crunchbase reported $8.5 billion in defense tech funding in 2025, a record high. In Europe, the Financial Times described growing VC activity in AI and defense in 2025, related to sovereign security concerns. These trends are important for Q1 2026 market positioning because they support a broader thesis: VC money is increasingly following national capability agendas, not just TAM narratives of consumer software.

Geography remains a key differentiator. The U.S. captured an unusually high share of global VC funding in Q1 2026. Europe, while not leading in total amount, continues to produce significant AI funding, including what the Financial Times described as Europe's largest ever seed round—a new AI startup raising over $1 billion. China's VC scene shows a different pattern: Reuters reported Chinese VC fundraising is expected to set a quarterly record, driven by state-led capital formation and policy pushes for AI/robotics, with government and state-owned entities being major limited partners.

The implication is: "Global VC" in 2026 is not one market but at least three partially independent machines—the U.S. system dominated by private super-rounds for frontier platforms, the Chinese system increasingly mediated by state capital allocation logic, and the European system maintaining innovation but constrained by expansion funding gaps, producing selective super-rounds rather than broad late-stage depth.

Outlook for the Second Half

The most useful way to think about the remainder of 2026 is scenario-based, as Q1's totals are异常 sensitive to classification and timing.

First, headline VC totals may remain high even if broad deal activity doesn't recover. Deal counts remain well below historical norms, while average round sizes are increasing. Q1 2026更像是 a continuation of this pattern rather than a reversal. If super-rounds continue, allocators might see "record VC funding" coexisting with emerging managers struggling to raise funds, seed funds lacking AI exposure being stuck, and founders outside thematic sectors finding it difficult to raise capital.

Second, valuation discipline is more likely to be tested than relaxed. Carta data shows that by Q4 2025, early-stage valuations hit records, with median post-money seed valuation reaching $24 million and Series A reaching $78.7 million, while the top 10% of U.S. startups on the platform took about half of the funding in 2025. This combination has historically been associated with greater outcome dispersion: companies perceived as category leaders command higher entry prices, while median companies face greater pressure to shut down or consolidate.

Third, the exit environment has improved in aggregate but remains fragile in terms of execution windows. Global exit activity has recovered from the trough, aided by IPO resumptions and continued M&A, but fundraising conditions remain weak, and public market volatility could close windows at any time. In early 2026, Crunchbase noted market volatility delayed some listing processes, even as private funding surged. The practical implication is that 2026 exits may still be uneven: open for elite assets, intermittently closed for others.

Fourth, for crypto investors and founders, the core question is whether crypto benefits from the AI-driven improvement in risk appetite or is crowded out by it. Current evidence is mixed. On one hand, stablecoin and payment projects are raising meaningful rounds and attracting mainstream VCs. On the other hand, the absolute scale of AI funding and its ability to attract sovereign, corporate, and strategic capital might draw marginal funds away from mid-sized crypto opportunities.

From insights4vc's perspective, the most noteworthy signals to watch for the remainder of 2026 are: Can crypto funding expand from channel infrastructure to genuine consumer adoption? Can tokenization move from pilot projects to repeatable institutional workflows? The direction is constructive, especially in payments, custody, compliance, and tokenized financial infrastructure, but regulatory and prudential hurdles may still slow actual deployment despite rising investor interest.

Conclusion

Q1 2026 is less a broad recovery of venture capital and more the emergence of a new funding paradigm. Record headline numbers are driven by a small group of AI and compute-intensive platforms at unprecedented scale, while the underlying deal breadth is far weaker than the surface numbers suggest. Crypto improved, but mainly in areas related to regulated financial infrastructure, not broad speculative demand. For investors and founders, the signal is clear: VC in 2026 is increasingly defined by concentration, selectivity, and widening dispersion, not a uniform recovery.

Trending Cryptos

Related Questions

QWhat percentage of global venture capital funding in Q1 2026 went to AI-related companies, and what was the total amount?

A80% of global venture capital funding in Q1 2026 went to AI-related companies, totaling approximately $242 billion.

QWhich four companies accounted for about two-thirds of the global venture capital funding in Q1 2026, and what were their funding amounts?

AThe four companies were OpenAI ($122 billion), Anthropic ($30 billion), xAI ($20 billion), and Waymo ($16 billion). Together, they accounted for about 65% of global VC funding.

QHow did the crypto/Web3 venture capital funding perform in Q1 2026, and what was a key characteristic of the investments?

ACrypto/Web3 venture capital saw an improvement with approximately $8.632 billion raised in Q1 2026. A key characteristic was that the funding was highly concentrated, with about two-thirds of it occurring in March, and it was primarily directed towards regulated, utility-focused infrastructure like stablecoin payments and compliance, rather than speculative projects.

QAccording to the article, what was a significant shift in the venture capital market's structure in Q1 2026?

AA significant shift was the market's transformation into a 'barbell structure,' where an unprecedented amount of capital was concentrated in a few global strategic AI platforms, while broader deal activity remained subdued, and fundraising for most funds was still difficult.

QWhat rationale did investors have for the massive funding rounds in AI companies like Anthropic, beyond just the potential of frontier models?

AInvestors were motivated by the companies' accelerating commercial traction and revenue generation. For example, Anthropic's annualized revenue reportedly grew to around $19 billion, with strong performance from products like Claude Code. This demonstrated a clear path to monetization, making it an attractive investment based on current commercial performance, not just future potential.

Related Reads

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

Ethereum Q1 2026 Report: Fees Down, Users & Transactions Hit New Highs Token Terminal's Q1 2026 report on Ethereum presents a pivotal development: the network achieved record highs in monthly active users (13.2M, +85.9% YoY), total transactions (200.4M, +81.5% YoY), and throughput (25.78 TPS), while transaction fees on the mainnet plummeted by 47.9% quarter-over-quarter. This shift is attributed to the network's strategic move into a "low fees for scale" phase, exemplified by the Fusaka upgrade which increased data capacity and lowered block space costs, releasing pent-up demand (a manifestation of Jevons's Paradox). The report highlights a core narrative shift for Ethereum: from a DeFi-centric blockchain to a global financial settlement layer. It maintains a dominant position in tokenized assets, holding majority market shares among top chains in stablecoins (61.8%), tokenized funds (73.0%), and tokenized commodities (84.0%). Growth in tokenized funds (+73.1% YoY) and commodities (+325.9% YoY) was particularly strong, driven by institutions like BlackRock and JPMorgan entering the space. Contrasting these usage gains, several USD-denominated value metrics declined in Q1: fully diluted market cap fell 30.3% QoQ, total value locked (TVL) dropped 11.0%, and ecosystem transaction volume decreased 24.0%. The report interprets this as Ethereum prioritizing long-term network expansion and cementing its role as the default settlement layer for finance over short-term fee capture. The commentary from Etherealize argues that, much like the early internet, Ethereum's open, permissionless model is poised to win over closed alternatives as institutional tokenization accelerates.

marsbit1h ago

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

marsbit1h ago

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

Pete Florence, a former senior research scientist at Google DeepMind and a key contributor to the Vision-Language-Action (VLA) model architecture, is deliberately distancing his startup, Generalist AI, from the trendy "world model" label. He argues that the industry should prioritize concrete goals over buzzwords. His goal is to create robots that can perform a vast range of unseen tasks with high speed and success rates, without needing task-specific training data. Recently, his company raised $400 million (¥2.7 billion) at a $2 billion valuation. Notable investors include NVIDIA's NVentures, Bezos Expeditions, NFDG, as well as Xiaomi co-founder Lin Bin, Zoom founder Eric Yuan, and renowned AI scientist Fei-Fei Li. Florence's approach stems from his academic background at MIT under Professor Russ Tedrake, focusing on understanding the physical world. After joining DeepMind, he developed models like Transporter Network and co-created the VLA framework. He left in 2025 to found Generalist AI. The company has launched two models: GEN-0, which demonstrated that scaling laws apply to physical motion, and GEN-1. GEN-1 was trained on over 500,000 hours of physical interaction data collected via a specialized wearable device. It achieves a 99% success rate on precise mechanical tasks like folding boxes and maintains performance three times faster than its predecessor. Florence believes GEN-1 is reaching a commercial utility threshold similar to the GPT-3 inflection point. The substantial funding round, following GEN-1's release, signifies strong investor confidence in Generalist AI's practical, goal-driven path to creating versatile, useful robots, regardless of the "world model" terminology.

marsbit1h ago

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

marsbit1h ago

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

In three days, Google lost two AI legends. On June 18, Noam Shazeer, co-author of the seminal "Attention is All You Need" paper and Gemini co-lead, left for OpenAI. Just 48 hours later, John Jumper, 2024 Nobel laureate and AlphaFold lead, departed DeepMind for Anthropic. This follows Andrej Karpathy joining Anthropic in May. These moves highlight a structural trend: top AI talent is concentrating at mission-driven, pre-IPO firms like OpenAI and Anthropic, while Google becomes a primary source. The exodus stems from a core mission mismatch. Google's ad-centric model often subordinates AI research to product and revenue goals, creating friction for pioneers like Shazeer, who returned in 2024 only to leave again. In contrast, OpenAI and Anthropic offer singular focus on pushing AI boundaries, whether towards AGI or safety-aligned models, which deeply appeals to top researchers like Jumper. Financial incentives amplify the pull. With both OpenAI and Anthropic nearing IPO, employees stand to gain immensely from equity, an upside Google's mature stock cannot match. Furthermore, the 2023 merger of Google Brain and DeepMind, intended to consolidate strength, has instead created cultural tension and slowed the path from research to product, as evidenced by Gemini's pace. This talent redistribution is reshaping the AI landscape. While Google retains vast data and compute resources, its true crisis is the quiet, continuous loss of the people who define the field's future. The real moat in AI is not infrastructure, but the concentration of brilliant minds—a battle Google is currently losing.

marsbit3h ago

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

marsbit3h ago

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

Beyond the familiar performance charts like MMLU-Pro and MMMU, which major AI models strive to ace, stands a key "examiner": Chinese-Canadian researcher Wenhu Chen. An assistant professor at the University of Waterloo and founder of TIGERLab, Chen addresses the crucial need for more rigorous AI evaluation. As models like GPT-4 began scoring near-perfect results on older benchmarks like MMLU, it became difficult to distinguish their true capabilities. In response, Chen introduced MMLU-Pro in 2024, featuring harder, more reasoning-focused questions with more answer choices, successfully reintroducing meaningful performance gaps. His work extends to multi-modal evaluation with MMMU and its enhanced version, MMMU-Pro. These benchmarks test a model's ability to understand and reason with complex information from images, charts, and text across diverse academic subjects, exposing the significant challenges even top models face in genuine comprehension. Chen's background in complex QA, table reasoning, and his experience at Google DeepMind on projects like Gemini inform his approach. He understands that effective benchmarks must anticipate how models might "cheat" by memorizing data or avoiding visual analysis. His lab also actively researches video understanding and generation models (e.g., UniVideo, Vamba), ensuring his evaluation work is grounded in practical model-building challenges. Now at Meta's Super Intelligence Lab, Chen continues his focus on multi-modal data and evaluation, representing the deep yet often unseen contributions of Chinese talent in shaping the fundamental tools of the AI industry.

marsbit3h ago

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

marsbit3h ago

Trading

Spot
Futures

Hot Articles

How to Buy ONE

Welcome to HTX.com! We've made purchasing Harmony (ONE) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy Harmony (ONE) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your Harmony (ONE)After purchasing your Harmony (ONE), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade Harmony (ONE)Easily trade Harmony (ONE) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

3.9k Total ViewsPublished 2024.03.29Updated 2026.06.02

How to Buy ONE

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 ONE (ONE) are presented below.

活动图片