Data Analysis How Much Does Raydium Really Rely on pump.fun?
Original Title: "Data Analysis: How Dependent Is Raydium on pump.fun?"
Original Author: Azuma, Odaily Planet Daily
The mainstream DEX protocol on Solana, Raydium (RAY), experienced a sharp decline today, directly triggered by pump.fun seemingly testing its own AMM liquidity pool. The market speculates that this move may lead to future pump.fun ecosystem tokens not being pooled on Raydium after breaking out of the "seed round," but instead being directly diverted to the pump.fun protocol, resulting in a reduction in Raydium's trading volume, corresponding revenue, and buyback amount.
Logic Behind RAY's Decline (Readers familiar with the relevant logic can skip this section)
Let's briefly outline the relationship between Raydium and pump.fun.
As the current leading meme token launchpad platform on Solana, the issuance of pump.fun's token goes through two stages: "seed round" and "public round." After the token is issued, it will first enter the "seed round" trading phase, which relies on pump.fun's protocol's own Bonding Curve for matching transactions. When the trading volume reaches $69,000, it will then enter the "public round" trading phase, at which point liquidity will migrate to Raydium, where a pool will be created and trading will continue.
Next, let's look at Raydium and RAY.
Currently, Raydium charges a 0.25% fee per transaction, with 0.22% allocated to Raydium's liquidity providers (LP) and 0.03% used for RAY buyback and ecosystem support. In summary, Raydium's trading volume will indirectly affect RAY's price through fee revenue.
So the current situation is that if pump.fun builds its own AMM, liquidity will no longer migrate to Raydium in the future, thereby reducing the latter's trading volume, fees, and consequently affecting RAY's value performance.
How Dependent Is Raydium on pump.fun?
Today, there has already been a lot of analysis in the market on the above points. However, it seems that no one has carefully examined how much Raydium relies on pump.fun in terms of trading volume. Therefore, we queried some data sources on Defillama and Dune, and the conclusion is shown in the following figure.

As can be seen from the above chart, in the past 14 weeks, the trading volume of the pump.fun token on Raydium has generally accounted for around 20%. This means that if pump.fun does indeed redirect trading volume from Raydium in the future through its own AMM (excluding autonomous liquidity migration activities due to uncertain platform fee rate differences), Raydium is expected to experience around a 20% reduction in trading volume.
Oversold?
Turning back to the market situation, OKX data shows that RAY dropped to a low of $2.82 today, corresponding to a decrease of over 30% (the data was delayed, but in hindsight, there was indeed some overselling at that time). The current price has gradually recovered to $3.15, representing a 25.43% decrease.
Considering that SOL also experienced a 5.8% decrease, RAY's current decline is basically within a reasonable range, meaning that the market has preemptively priced in pump.fun's frontrunning behavior.
Let's end with a quote from Fluid COO DMH:
“RAY's plummet once again proves to us that ‘distribution >>> tech.’ Both the traditional world (Microsoft) and the crypto space (Metamask) have countless examples showing that if you have a large enough user base, your product isn't that important.”
You may also like

How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Ritmex demonstrates how disciplined risk control and structured signals can make an AI crypto trading bot more stable and reliable on WEEX, highlighting the importance of combining execution discipline with scalable AI trading systems.

Old Indicator Fails, Three Major New Signals Emerge: BTC True Bottom May Still Be Below $60K

Meeting OpenClaw Founder at a Hackathon: What Else Can Lobsters Do?

Huang Renxun's Latest Podcast Transcript: NVIDIA's Future, Embodied Intelligence and Agent Development, Soaring Demand for Inferencing, and AI's PR Crisis
How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Crypto_Trade shows how structured inputs and controlled adaptability can build a more stable and reliable AI crypto trading bot within the WEEX AI Trading Hackathon, highlighting a practical path toward scalable AI trading systems.

AI Starts to Devour the Manufacturing Industry | Rewire News Morning Edition

When Scaling Meets Speed, Ethereum Foundation Introduces "Hardness" to Safeguard the Base Layer

Google, Circle, Stripe Flock Together to Let AI Spend Money: Payment Giants' Joys and Worries in 2026 Q1

$100 Billion Factory Purchase: Bezos and Middle Eastern Capital Shift AI Money from Cloud to Shop Floor

Xiaomi and MiniMax both unleash their ultimate moves, signaling the start of the Agent Pricing War.

Predicting markets has taken the spotlight, but the Perp DEX has been quietly waging war on traditional exchanges.

Is the Market Slump Still Making Millions a Day? Is pump.fun's Revenue Real?

Understanding x402 and MPP in One Article: The Two Paths of Agent Payments

Quick Look at the Latest 18 Graduation Projects from Alliance: Who's the Next Pump.fun?

It's not just the prediction market that profits from the Iraq War

The "bank card" of AI has caught the attention of the giants

Morning News | U.S. SEC approves tokenized trading on Nasdaq; Animoca Brands announces investment in AVAX tokens; Algorand Foundation completes strategic integration

$70 trillion wealth transfer, the financial gateway is being rewritten | Interview with Robinhood CEO Vlad Tenev
How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Ritmex demonstrates how disciplined risk control and structured signals can make an AI crypto trading bot more stable and reliable on WEEX, highlighting the importance of combining execution discipline with scalable AI trading systems.
Old Indicator Fails, Three Major New Signals Emerge: BTC True Bottom May Still Be Below $60K
Meeting OpenClaw Founder at a Hackathon: What Else Can Lobsters Do?
Huang Renxun's Latest Podcast Transcript: NVIDIA's Future, Embodied Intelligence and Agent Development, Soaring Demand for Inferencing, and AI's PR Crisis
How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Crypto_Trade shows how structured inputs and controlled adaptability can build a more stable and reliable AI crypto trading bot within the WEEX AI Trading Hackathon, highlighting a practical path toward scalable AI trading systems.