Will Solana Flip Ethereum Soon? SOL Takes First Step Toward Total Domination

bitcoinistPublished on 2026-04-21Last updated on 2026-04-21

Abstract

Solana has significantly closed the gap with Ethereum, particularly in transaction volume, processing 9 billion transactions last month compared to Ethereum's 69 million. It has also surpassed Ethereum in cumulative lifetime transactions. This highlights Solana's high-throughput, low-cost architecture designed for real-time usage. Major partnerships, such as with Visa for stablecoin settlements and Western Union's upcoming stablecoin launch, underscore its growing institutional adoption. Solana has even overtaken Ethereum in real-world asset (RWA) holders. However, a complete "flippening" depends on broader factors like capital inflows, developer activity, and network confidence. While Solana's smaller market cap suggests greater growth potential, Ethereum's Layer-2 scaling strategy strengthens its ecosystem. The outcome remains uncertain, with trade-offs on both sides.

Solana has long stood as Ethereum’s closest rival across nearly every segment, even though its price performance has not always kept pace. From DeFi to user activity, SOL has been behind Ethereum every step of the way.

What used to be a debate about potential now looks more like a measurable race. That conversation between Solana and Ethereum has grown considerably more serious in 2026, and the numbers behind it are not theoretical, especially when it comes to the number of transactions processed on each network.

Transaction Gap Between Solana And Ethereum

A single metric is changing how analysts frame the rivalry between Ethereum and Solana. The interesting metric in question is the raw transaction volume processed on each network.

SOL processed nearly 9 billion transactions last month, compared to just 69 million on Ethereum. The numbers are so lopsided that Solana, which is roughly five years younger than Ethereum, has already surpassed its rival in cumulative lifetime transactions, processing over 500 billion total to Ethereum’s 3 billion.

That difference is not just about numbers. It shows how SOL is positioning itself as a high-throughput network built for real-time usage. The architecture allows thousands of transactions per second at low cost, creating an environment where activity can grow quickly without the bottlenecks that Ethereum had. Although the Ethereum network has since been upgraded to process more transactions, it hasn’t been enough to upend SOL.

Can SOL Actually Flip ETH?

Solana has been the go-to hub for institutions looking for a faster network with high throughput. For instance, the payments giant Visa is in a stablecoin settlement partnership with Solana, placing it at the heart of the growing blockchain payments niche.

Another example is Western Union, which is on track to launch its USDPT stablecoin on SOL sometime in the first half of 2026, bringing access to its $150 billion in annual remittance volume to the network.

Recent data shows that SOL has, for the first time, recently overtook Ethereum in total real-world asset (RWA) holders. However, a true flippening goes beyond isolated metrics and speaks to a change in capital inflows, developer activity, and confidence in the network.

Solana’s smaller market capitalization compared to Ethereum means that there is more room for upside, which makes it a better buy in terms of returns. Still, the gap is not just technical, and the question of whether Solana will flip Ethereum completely is a question that currently has no obvious answer.

Ethereum developers have leaned into Layer-2 scaling, effectively outsourcing transaction load. This strategy may reduce visible activity on Ethereum itself, but it strengthens its overall ecosystem. There are also trade-offs on Solana’s side. Its quick growth has been tied in part to high-frequency activity, including memecoins on the network.

SOL trading at $85 on the 1D chart | Source: SOLUSDT on Tradingview.com

Related Questions

QWhat key metric is changing how analysts view the rivalry between Solana and Ethereum?

AThe raw transaction volume processed on each network, with Solana processing nearly 9 billion transactions last month compared to Ethereum's 69 million.

QHow does Solana's cumulative lifetime transaction count compare to Ethereum's?

ASolana has processed over 500 billion cumulative lifetime transactions, which surpasses Ethereum's 3 billion.

QWhat are two major financial institutions mentioned that are partnering with or using the Solana network?

AVisa, which has a stablecoin settlement partnership with Solana, and Western Union, which is launching its USDPT stablecoin on Solana in 2026.

QIn which specific metric did Solana recently overtake Ethereum for the first time?

ASolana recently overtook Ethereum in total real-world asset (RWA) holders.

QWhat is one potential trade-off mentioned regarding Solana's rapid growth?

AIts quick growth has been tied to high-frequency activity, including memecoins on the network.

Related Reads

Dialogue with a Macro Analyst: AI Drains All Liquidity from U.S. Stocks, $40K Bitcoin is the True Bottom

In a recent discussion, macro strategist Luke Groman, founder of FFT LC, presented a sobering analysis of current markets. He argues that while the S&P 500 hits new highs, this is largely driven by just seven AI stocks, which are "sucking all the oxygen and liquidity out of the room." Bitcoin, which he calls the "last working smoke alarm for liquidity," is signaling trouble, having entered a difficult period. Groman explains that the AI boom is fueled by accounting practices that front-load revenue, creating an illusion of high profits while cash is being depleted. He warns this cycle could reverse sharply when construction slows. His base case is that stocks will rise in dollar terms but fall significantly when measured in gold or Bitcoin, highlighting that long-term US Treasury futures have already lost 90% of their value against gold over the past decade. He points to major structural risks, including China's dominance in rare earths—a small commodity market underpinning trillions in tech stock value—and the prolonged closure of the Strait of Hormuz, which he calls a "Suez Moment" for the US. This, combined with a shift towards a "no ticky, no washy" proof-of-work system for settling trade (using gold, not trust), signals deeper systemic distrust. Regarding US debt, Groman notes that historically, all 58 countries that reached a 130% debt-to-GDP ratio defaulted, primarily through inflation. The US crossed this threshold in 2020. He also highlights a contradiction in the AI narrative: if it's as transformative as claimed, it must destroy white-collar jobs, threatening half of US tax revenue—a reality at odds with the "no job loss" messaging from tech leaders. On Bitcoin, Groman sold most of his position near the top and hasn't fully re-entered. Citing technical analysis from Northstar Bad Charts, he suggests a potential bottom around $40,000 could materialize in Q3 or Q4. He concludes that while he may be labeled a doomsayer, his view is simply realistic, grounded in historical precedents and current macro pressures.

marsbit13m ago

Dialogue with a Macro Analyst: AI Drains All Liquidity from U.S. Stocks, $40K Bitcoin is the True Bottom

marsbit13m ago

Apple's Desired On-Device AI Sees a Dark Horse Emerge: The First Cognitive Model is Born, 4B Matches GPT-5.4

A Chinese company, Tomorrow's Journey (Nextie), has introduced what it is calling the industry's first "cognitive model" for edge devices. Named New Journey Alpha, this 4-billion-parameter model reportedly matches the performance of trillion-parameter giants like GPT-5.4 in group intelligence tasks such as debate and collective decision-making. The development follows Andrej Karpathy's vision of stripping vast factual knowledge from large language models to retain only a smaller "cognitive core" capable of reasoning, planning, and knowing its own limits. This approach directly addresses the soaring computational costs and token expenses hindering AI's widespread deployment, as highlighted by incidents like Amazon shutting down an internal AI tool due to prohibitive costs. Trained via reinforcement learning on a corpus of academic papers from 1800-2020 to enhance generalization, the model enables three key advancements: 1) Improved decision quality in multi-agent systems, 2) Drastically reduced compute costs, allowing for cost-effective cloud or on-device (e.g., MacBook) deployment, and 3) The feasibility of "proactive" AI agents that act autonomously without user prompts, unlocking new commercial possibilities beyond today's reactive models. Built by the former Microsoft Xiaoice team—known for creating a 3.6B model that outperformed a 65B Llama model—the company is now focusing on the multi-agent systems sector, a field gaining significant investor interest. The model's economic impact is profound; by achieving high-level performance with minimal parameters, it fundamentally alters the cost structure of AI services, challenging the prevailing model of ever-larger parameter counts.

marsbit3h ago

Apple's Desired On-Device AI Sees a Dark Horse Emerge: The First Cognitive Model is Born, 4B Matches GPT-5.4

marsbit3h 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