How MegaETH targets 15K–35K TPS in 7-day mainnet stress test

ambcryptoОпубликовано 2026-01-21Обновлено 2026-01-21

Введение

MegaETH, a real-time EVM-compatible blockchain, is launching its mainnet on January 22nd with a 7-day stress test aiming to process 11 billion transactions. The project targets a sustained throughput of 15,000–35,000 transactions per second (TPS), having achieved nearly 47,000 TPS in testing. It also boasts a 10-millisecond block time, significantly faster than other blockchains. While prioritizing speed and low latency, concerns about decentralization and potential censorship risks due to centralized sequencing have been noted. The stress test will involve user interaction with gaming applications and backend transactions through a decentralized exchange. Following the test, the public mainnet will launch alongside select DeFi and consumer applications.

MegaETH, the real-time EVM-compatible blockchain, announced that it will launch its mainnet on the 22nd of January. Dubbed the MegaETH stress test, it aims to process 11 billion transactions in 7 days.

They were ” opening mainnet to users for several latency-sensitive apps while the chain is under intense, sustained load.”

The project aims to achieve performance levels comparable to high-speed blockchains such as Solana [SOL] while also providing extremely low latency and high throughput.

It has achieved nearly 47k transactions per second (TPS), noted growthepie in a post on X. MegaETH was targeting a sustained, true TPS of 15k-35k across the 7 days of the stress test.

“In the end, MegaETH will have the largest tx count in history across all EVM chains while users frictionlessly play with the chain.”

Messari reported that the MegaETH testnet achieved a 10‐millisecond block time, far faster than any other blockchain.

While the design prioritizes speed, the report raised concerns about decentralization and potential censorship risks due to centralized sequencing.

MegaETH to push the boundaries of blockchain capabilities

“Stress tests only matter if they’re uncomfortable”, said the blockchain’s post on X. During the test, users can interact with gaming applications such as Stomp.gg, Smasher.fun, and Crossy Fluffle.

On the backend, the team will push a mix of ETH transfers and v3 automated market maker swaps through the decentralized exchange Kumbaya.xyz.

The public mainnet will launch after the global stress test. A selection of day-one DeFi and consumer applications powered by its native stablecoin, USDm, will also be launching.

Messari also documented that in October 2025, MegaETH raised $50 million during the MEGA token sale, which became oversubscribed within minutes. This figure was part of the nearly $75 million raised from various grassroots funding efforts.


Final Thoughts

  • MegaETH is an EVM-compatible blockchain aiming to deliver real-time crypto performance, with a 10 ms blocktime and nearly 47k TPS in testing.
  • The global stress test targets a total of 11 billion transactions in 7 days, starting on the 22nd of January.

Связанные с этим вопросы

QWhat is the main goal of MegaETH's 7-day mainnet stress test starting on January 22nd?

AThe main goal is to process 11 billion transactions in 7 days, targeting a sustained true TPS of 15,000-35,000.

QWhat key performance metrics has MegaETH achieved in testing according to the article?

AMegaETH has achieved nearly 47,000 TPS and a 10-millisecond block time in testing.

QWhat are some of the applications users can interact with during the MegaETH stress test?

AUsers can interact with gaming applications such as Stomp.gg, Smasher.fun, and Crossy Fluffle.

QWhat concerns did the Messari report raise about MegaETH's design?

AThe report raised concerns about decentralization and potential censorship risks due to centralized sequencing.

QHow much funding did MegaETH raise during its MEGA token sale in October 2025?

AMegaETH raised $50 million during the MEGA token sale, which was part of nearly $75 million raised from various grassroots funding efforts.

Похожее

South Korean Stocks Plunge, Global Funds Liquidate: Has the Semiconductor Fundamentals Really Changed?

South Korean stocks experienced their sharpest decline of the year, with the KOSPI index plunging nearly 9% on Monday, triggering a market circuit breaker. Leading semiconductor firms Samsung Electronics and SK Hynix were heavily sold off, raising questions about whether the AI-driven bull market has reached an inflection point. This sell-off was largely triggered by a significant drop in the U.S. semiconductor sector late last week. Concurrently, NVIDIA CEO Jensen Huang visited Seoul over the weekend, meeting with top executives from SK Group, Samsung, LG, and NAVER. He announced a new multi-year partnership with SK Hynix to co-develop next-generation memory products for AI data centers. Huang emphasized that AI infrastructure build-out remains in its early stages, creating a stark contrast between market panic and ongoing, strengthened industry collaboration. The article argues that South Korea has become one of the most sensitive markets for global AI-related capital flows, functioning like a large AI memory ETF due to the heavy weighting of its chipmakers. The current market turmoil reflects a shift in investor focus: from simply betting on overall AI growth to scrutinizing which companies will actually capture the profits from that growth. This "profit pool reassessment" phase is causing high volatility based on supply chain news and earnings guidance. Ultimately, the direction of the Korean market will be determined by external factors—NVIDIA's orders, HBM supply-demand dynamics, and capital expenditures from cloud service providers—rather than domestic conditions. The disconnect between sharp price corrections and continued strong signals from the industry core leaves the market at a crossroads, awaiting clearer data on the durability of AI infrastructure demand.

marsbit11 мин. назад

South Korean Stocks Plunge, Global Funds Liquidate: Has the Semiconductor Fundamentals Really Changed?

marsbit11 мин. назад

Trump in Talks with AI Companies Over Profit Sharing, A Narrative Pressure of Industrial Revolution Scale Begins

In recent AI market discussions, a new dimension beyond growth and profits has emerged: the question of how the immense wealth potentially generated by AI should be shared with the wider public. Triggered by reports of White House officials discussing "voluntary equity transfers" with top AI firms, similar to models like Alaska's Permanent Fund, the conversation focuses on public wealth funds. OpenAI's own whitepaper proposes such funds, allowing households without direct tech stock ownership to benefit from AI gains. More radical proposals, like Bernie Sanders' call for high public equity stakes and board seats, represent an extreme end of the spectrum. Currently, these are early-stage policy probes, not enacted laws. OpenAI's initiative is seen as an attempt to secure "social license" for its future expansion, mitigating risks of public backlash, stricter regulation, or anti-trust actions as AI's economic impact grows. The core market implication is the introduction of a "policy discount" to AI valuations, particularly for private model companies like OpenAI, Anthropic, and xAI. Investors must now consider not just future earnings but also what portion might be allocated to public mechanisms. The impact varies greatly based on the mechanism. A small, voluntary transfer of non-voting economic rights (e.g., 5%) acts as a quantifiable long-term cost. Government acquisition of economic rights via warrants tied to support differs from direct equity with governance power. The most disruptive scenario would be forced high-percentage public ownership affecting control and innovation incentives. Key signals to watch include whether other AI companies follow suit, if the White House formalizes proposals, related disclosures in future IPO documents, and any market price reactions. For now, this represents a shift from pricing pure AI growth to pricing its potential distribution. A manageable, voluntary economic share is akin to an insurance cost for societal acceptance, while a forced shift toward control and governance would fundamentally alter valuation logic.

marsbit15 мин. назад

Trump in Talks with AI Companies Over Profit Sharing, A Narrative Pressure of Industrial Revolution Scale Begins

marsbit15 мин. назад

From Record Highs to a Two-Week Low: Why Did AI Concept Stocks Suddenly Pull Back?

From Record Highs to Two-Week Lows: Why Did AI Stocks Suddenly Pull Back? U.S. stock indices, led by the tech-heavy Nasdaq 100, fell sharply to two-week lows. This marked a reversal from earlier in the week when AI infrastructure and semiconductor stocks had propelled major indices to record highs. Investors are rotating out of these previously high-flying tech sectors into other areas. The sell-off was driven by profit-taking and concerns that the AI rally had become overextended, exacerbated by chipmaker Broadcom's sales outlook falling short of lofty market expectations. The decline accelerated following a stronger-than-expected U.S. May nonfarm payrolls report, which showed 172,000 jobs added versus an estimated 88,000. This data sparked a jump in bond yields, with the 10-year Treasury yield rising to 4.553%, as it reinforced market speculation that the Federal Reserve's next move could be a rate hike rather than a cut. Globally, equities also declined, with European and Asian markets falling. Within the U.S. market, chip and AI-related stocks like Super Micro Computer and Arm Holdings led the losses, dropping over 7%. Cryptocurrency-linked stocks and mining shares also fell sharply amid drops in Bitcoin and commodity prices. While the overall Q1 earnings season remained solid, with 83% of S&P 500 companies beating estimates, the weakness was concentrated in tech. Excluding the tech sector, Q1 earnings growth was around 3%, the weakest in two years.

marsbit15 мин. назад

From Record Highs to a Two-Week Low: Why Did AI Concept Stocks Suddenly Pull Back?

marsbit15 мин. назад

JP Morgan Mid-Year Research Report Analysis: The AI Supercycle is Not Over, Reduce Cash Holdings + Allocate to Real Assets

JP Morgan's 2026 Mid-Year Outlook argues the AI supercycle is far from over, despite market pessimism. The report advises clients to reduce cash holdings, increase allocations to real assets as an inflation hedge, and focus on emerging markets. Key conclusions include: 1. **AI Supercycle Intact**: Hyperscalers' 2026 capex forecasts exceed $650B, with AI contributing to GDP growth. However, their financial profile is shifting toward heavy investment, compressing free cash flow. 2. **SaaS Disruption**: Traditional software companies are being negatively impacted by AI, with significant stock declines and pressure in credit markets. 3. **Persistent Inflation**: Core inflation is structurally higher post-pandemic. Holding excess cash and bonds leads to real wealth erosion. Recommendations include commodities, infrastructure, real estate, and gold. 4. **Geopolitical Shocks & Opportunities**: The Hormuz Strait blockade caused a major oil shock, but JP Morgan views the subsequent equity market pullback as a buying opportunity. "Fragmentation" is creating pockets of value, notably in resource-rich Latin America, AI-supply-chain-linked East Asia, and deeply discounted Chinese equities, where a policy shift could trigger a re-rating. 5. **Regional Views**: The firm is cautious on Europe due to high energy costs and lower innovation investment, preferring US and select EM exposures. In short, JP Morgan sees market volatility as an entry point but recommends a portfolio pivot: favor AI infrastructure, real assets, and EM, while avoiding excess cash, vulnerable software firms, and traditional 60/40 stock-bond allocations.

marsbit40 мин. назад

JP Morgan Mid-Year Research Report Analysis: The AI Supercycle is Not Over, Reduce Cash Holdings + Allocate to Real Assets

marsbit40 мин. назад

Торговля

Спот
Фьючерсы
活动图片