Real Vision Founder: Why Do Most Public Chains Struggle to Survive?

Original Author: Raoul Pal, Founder of Real Vision

Compiled by: Chopper, Foresight News

In your portfolio, there is definitely a public chain that you bought in the last cycle because you thought it would become the next Ethereum. Better technology, combined with the founder's persuasive comments on podcasts… Your initial purchase was not foolish; many smart people did the same.

But looking back now, this chain has basically become a ghost town. Only a few validation nodes are still running, with hundreds of wallets transferring small tokens back and forth, and the token price is far below the purchase cost of its believers.

According to CoinGecko, as of the end of last year, over 13 million tokens have stopped trading, with the vast majority disappearing by 2025. Many of the public chains they rely on have also met the same fate.

Over the past thirteen years, I have seen similar opinions on social media during every bear market. Cryptocurrency is a scam; it has always been a casino, and I told you so long ago.

But this large-scale extinction is not a scandal; it is just basic probability.

I wrote this in December 2020, and at that time, I thought it was obvious, but others did not. Tokens are merely products of venture capital priced in real-time by market value. If you hold early seed round projects, and the target price is being repriced every second, you will see the same result: about 80% eventually go to zero, 19% can create some value, and only 1% earn the majority of the returns. The crypto market simply broadcasts this process live to everyone, and this real-time price fluctuation can easily cause panic.

At that time, I also used this standard to examine myself. If Real Vision had been assessing its valuation in real-time every day since its inception, I would guess its value has nearly dropped to zero about six times. The value of a project comes from its adoption rate, which ultimately comes from revenue; the vast majority of projects will never reach that stage. Most projects do not survive. This is the reality, whether you like it or not; this is capitalism.

So the real question has never been "Will most public chains disappear?" They are destined to disappear. The real thing to think about is: which ones can survive, and how to identify them before the price gives the answer.

We Have Witnessed the Same Script

Twenty-one years of writing experience has taught me to look for precedents, and the precedent to keep in mind here is the bursting of the internet bubble.

In November 2018, Bitcoin was in a deep bear market, and I wrote that this scene was extremely similar to the internet bubble of 2000 and 2001: grand ideas, but flawed business models. But in the end, there will be phoenixes rising from the ashes. I was certain that the crypto market would also replay this process, but I could not determine which projects were phoenixes and which were just ashes, and I honestly stated that at the time.

Admitting the inability to predict is the correct answer because in 2000, no one could pick the final winners. At that time, there was overbuilding of infrastructure, and the Nasdaq index plummeted 78% from its peak in two and a half years, with the vast majority of targets going to zero. But the few companies that rose from the ashes grew into the largest companies in the world, relying on the fiber optic infrastructure built by those bankrupt companies. Looking back, the crash was just an episode on the way up; being in it made people feel like the entire industry was coming to an end.

Since then, all major platform markets have ended up similarly. In the cloud computing field, there are only about five leading players left; the operating system and mobile phone sectors are similar, with the vast majority of value concentrated in the top four. Public chains are fundamentally the same as these platform markets.

A Public Chain is an Economy, Not Just a Token

Since it belongs to a platform market, what is its product? The answer is simple: block space.

Winners will make their block space more attractive through technology or narrative (or both), attracting more users and funds to circulate on the chain. Everything else is just marketing packaging.

This is why general-purpose public chains cannot be seen as a company, nor can they simply be treated as a token. Ethereum, Solana, and Sui are independent economies with their own GDP, money supply, and monetary policy. They should be evaluated like an economy—by looking at how much economic activity is generated on the chain.

Four Paths to Survival

The landscape of the sector is much simpler than everyone thinks; for a project to survive, there are only four paths:

First, become an independent economy. Ethereum, Solana, Sui, and a few other public chains have sufficient throughput, composability, and developer density to support a global token economy.

Second, pursue a vertical specialization route. Hyperliquid is the most typical example; it is an integrated exchange that just happens to use a public chain as its execution layer. Specialized exchanges can often be profitable, but their revenue ceiling is constrained by the niche market, and they should be valued like exchanges with deep moats, not like an unlimited open economy.

Third, operate as a layer two network. Build a business on top of a layer one public chain, renting the underlying security. Some layer two networks may become quality businesses, but they essentially belong to a franchise model, like stores opened on Shopify. Even if a certain layer two disappears, its on-chain state can be migrated elsewhere, which is why they cannot accumulate value like layer one public chains: layer one has data permanence, while layer two is merely renting.

The fourth category is somewhat special: BNB. The market prices it as an independent economy, but it is not. Because it is not decentralized, its true underlying security is Binance's balance sheet. It is a good business, but essentially a centralized platform token dressed in layer one clothing.

Why Most Public Chains Struggle to Survive

The vast majority of remaining public chains—those that launched in the last two cycles—do not belong to the four categories above. They are general-purpose public chains that want to compete with those independent economies but lack the conditions to win; they are not specialized enough to occupy a dedicated niche; and they are not centralized enough to rely on the balance sheet of a large platform. They are merely "a public chain." Public chains without a moat will ultimately see their value go to zero.

This is the structural root cause. On a practical level, what truly kills them is the token issuance mechanism.

Since the summer of 2024, I have been researching low circulation, high fully diluted valuation (FDV) tokens, and this pattern has not changed: the market dislikes these types of assets. Tokens often experience a sharp drop of 70% or more shortly after listing due to a small circulating supply, as the market anticipates subsequent unlocking selling pressure. In a bull market, if there is real demand behind it, low circulating supply tokens can skyrocket. But when a bear market arrives, unless the unlocking is nearly complete or the demand is genuinely sustainable, these types of assets will significantly underperform the market. And public chains without a moat never have real demand. They may gain short-term popularity, but converting that popularity into long-term adoption is difficult; the vast majority of hype is fleeting.

Thus, the issuance structure merely accelerates the process of these homogeneous public chains going to zero; even without the issuance mechanism issue, the market would ultimately yield the same result.

The Race Towards Zero Cost

The vast majority of valuation frameworks in the industry will fail here.

The core dimension of public chain competition is operational efficiency. In other words, the public chain that wins collaborative competition will inevitably push the marginal cost of each transaction towards zero. If you apply a cash flow discount model, the conclusion is that leading public chains are valued lower than challengers because they earn the least in transaction fees per transaction. This model gives a completely inverted answer.

To assess the value of a public chain, you need to think in reverse. Imagine if Ethereum were shut down, all layer two networks paralyzed, most stablecoin markets disappeared, and all DeFi, NFTs, and tokenized assets were impacted; the possibility of building the future financial system on this infrastructure would also cease to exist. This is the value of Ethereum. No one would assess the TCP/IP protocol by calculating the revenue of each data packet. To evaluate it, one looks at the entire internet that runs on it.

This competition will continue to accelerate, and a new class of users is about to enter the market. I previously explained that AI agents cannot use traditional banking systems and must rely on these on-chain channels for settlement. Agents have no inherent preferences and will automatically choose the cheapest, fastest, and most efficient network each time; once a lower-cost option is available, they will immediately leave the more expensive public chain. Solana and Sui have already pushed stablecoin transfer costs to nearly zero, which is a manifestation of Wright's Law unfolding before our eyes.

Some businesses require the underlying security of Ethereum, while others only pursue extreme speed. Therefore, different public chains serve different scenarios, and the market structure is dominated by the top players, rather than a single winner. But tail-end public chains do not have the qualification to share the pie.

Everyone Misunderstood the Measurement Metrics

I can explain why the industry's measurement standards are fundamentally flawed; I have fallen into this trap myself.

Earlier this year, I planned to build a valuation framework for layer one public chains, starting with fully diluted valuation, just like all analysts, using commonly tracked metrics: total value locked (TVL), fee revenue, DEX trading volume, and stablecoin market cap. The data correlation seemed high, and I thought I had found the right method.

But that was not the case; the entire logic was circular reasoning. The TVL valuation unit itself is the token to be valued; DEX trading volume fluctuates with speculative market conditions, and fee revenue varies with trading volume. It is equivalent to using data derived from token prices to explain token prices. What we observe is merely the surface, not the essence.

So I eliminated price interference and converted it into ratios unaffected by token prices. I selected the peak in January 2025, covering data from 12 public chains, and asked one question: Are there any indicators that can predict which public chains will have the smallest declines over the next 13 months?

Fee yield had no predictive power at all. Bull market fees can only reflect speculative enthusiasm, not measure real value creation. TVL/FDV (the crypto version of price-to-book ratio) is equally ineffective.

The only metric that has a correlation with asset returns is capital turnover rate: the speed at which capital circulates on chain exchanges. But the correlation is inverse. In January 2025, Solana's capital turnover rate reached 200 times its locked value, while Ethereum was only 7 times. The faster the capital turnover of a public chain, the worse it performed over the next 13 months; the public chains with more capital retention showed stronger resilience against declines.

Now my understanding is that turnover rate represents entropy increase, while capital stickiness represents order. When capital comes in and settles down, it is used for lending, exchanging, and re-staking, continuously establishing economic connections and attracting more capital into the market. Fast in-and-out capital merely treats the chain as a casino, and when the market cools, it leaves no residue. Therefore, the high trading volume that everyone chased at the peak of the bull market is actually a risk warning; those public chains that appear calm and have long-term capital retention can withstand declines better.

Characteristics of Survivors

From this, I summarize three key observation dimensions, all unrelated to price:

First, can the economic density of single users be maintained when the token price crashes? From the peak in December 2024 to February 2026, the price of a public chain token I tracked fell by 83%, TVL dropped by 78%, and the number of active addresses decreased by three-quarters. However, the deployed funds per active user remained almost unchanged: around $2,100 at the peak, and still $2,100 at the trough. Speculative visitors and bots exited, but the remaining users continued to engage in economic activities of similar scale. Among the public chains I tracked, only three Layer 1 chains maintained this density metric during the downturn: Ethereum, Solana, and Sui. All other public chains saw a simultaneous shrinkage in user economic density as the token price fell; one well-funded mainstream Layer 1 saw its user economic density shrink by 83%, meaning retained users basically stopped all on-chain activities.

By the way: I do work for the Sui Foundation. However, I only discovered that Sui was one of these three targets after completing the data analysis; the data does not lie.

Second, can the supply of stablecoins continue to grow during the token downturn? The value of on-chain USD stablecoins does not shrink with the tokens. If USD funds continue to flow in and settle during a bear market, it indicates a long-term choice by external capital. All three public chains saw an increase in stablecoin balances during the downturn, with the public chain that saw an 83% drop in token price still experiencing about a 50% growth in stablecoin size.

Third, the continuous influx of developers is also my highest-weighted metric. Developers are the most scarce capital in public chains. Users can withdraw all their invested funds within minutes; developers invest years learning specific languages and architectures, and the migration cost is extremely high. The continuous migration of developers to a particular public chain during a bear market represents a high-certainty choice made by the most knowledgeable professionals in the industry, despite the high switching costs. Price charts can never reflect this.

The growth of wallet numbers, the increase in on-chain transaction value, and the early entry of developers, along with the ability to maintain all these metrics during market pullbacks—this is what can transcend cycles. Only those that meet this condition are worth in-depth study; if not, what you hold is merely a homogenized commodity token.

The S-curve growth of such targets may experience a 90% price retracement midway. However, the few projects that survive will achieve exponential growth in the long term, continuously setting new highs. After thousands of projects undergo a life-and-death selection process, network effects take effect, and the entire ecosystem takes off.

There will be more and more projects in the long-tail track, with a large number of tokens issued in every cycle. Many people fantasize about finding a hundredfold token among the vast number of long-tail projects, while ignoring the mainline opportunities right in front of them. Focus on adoption rather than token price.

The vast majority of projects will eventually perish. The few that survive are the core of the entire game.