- Bitquery’s on-chain analysis of 8.98 million Pump.fun tokens found that 79% ceased all trading activity after their launch day, with only 1.5% still recording any trades by week five.
- Roughly one in 58 Pump.fun tokens graduated from the bonding curve to a PumpSwap pool, a figure broadly consistent with trader Bishaqs’s independent estimate of one in 70.
- Token issuance shows no signs of slowing, with MemeFees logging at least 21,765 launches across eight platforms on October 19 alone, led by Flap.sh and Pump.fun.
Bitquery Data Reveals 79% of Pump.fun Tokens Go Dark After Launch Day
A comprehensive on-chain study by blockchain analytics firm Bitquery has quantified just how brief the trading life of the typical Pump.fun token truly is. Tracking new Solana tokens from November 1, 2025 through October 7, 2026, Bitquery catalogued 8,984,141 tokens issued through Pump.fun, the Solana-based meme coin launchpad, and found that 79% of them never recorded another trade after the day they first went live. The analysis defines launch day as the date of a token’s first confirmed swap, and measures trading persistence rather than price performance — meaning the figure captures how long tokens retain any market activity, not how severely they declined in value or how many holders sustained losses.
The dropoff in activity is severe and rapid. Only 1.5% of Pump.fun tokens registered even a single trade during their fifth week of existence, and a mere 0.2% recorded at least 10 trades within that same window. Graduation — the milestone at which a bonding-curve token transitions to a PumpSwap liquidity pool — applied to approximately one in every 58 tokens in the sample. Pump.fun’s dominance of overall issuance is equally striking: of roughly 11.5 million new Solana tokens with a confirmed first trade across the entire observation period, 78% originated on Pump.fun. Tokens that never traded at all, and those whose first swap occurred in a pre-existing long-standing pool, were excluded from the dataset. Bitquery’s methodology counts all successful swaps, including automated trades, and discloses missing blocks alongside coverage gaps for newer trade formats.
Cross-Platform Comparison: Meteora and Raydium Show Similar Patterns at Different Intensities
Comparable launchpad platforms produced broadly similar survival curves, though at varying intensities. Launch-day-only trading reached 51% for tokens issued through Meteora’s Dynamic Bonding Curve and 84% for Raydium LaunchLab tokens. By week five, 1.9% of Meteora tokens and 1.3% of Raydium tokens were still recording trades — modestly higher persistence rates than Pump.fun’s 1.5%. Bitquery explicitly cautions, however, that sample structures differ across platforms, meaning the gaps between venues cannot on their own establish why one launchpad outperforms another in terms of trading longevity. Each platform’s dataset carries its own coverage limitations, making direct cross-platform conclusions unreliable without accounting for those structural differences.
Binance Founder CZ Warns AI Could Threaten Crypto Security Without Breaking Bitcoin Encryption
Jumpbit’s Separate Study Adds Further Dimension to the Survival Picture
A separate September study conducted by Jumpbit examined 1,083,771 Pump.fun launches — approximately 36,100 per day — using the dydt Solana trade index to follow trading activity through October 12. Jumpbit’s findings showed that 95.1% of launches recorded at least one trade, yet only 17.2% had a last recorded trade at least 24 hours after launch, and just 7.5% sustained activity for at least seven days. A mere 0.5% were still trading during the final 24 hours of the observation window. Jumpbit’s methodology differs from Bitquery’s in one key respect: it counts a token creator’s own first purchase as a valid trade, and notes that a token can continue registering activity even when its price is effectively near zero. As a result, Jumpbit’s numbers answer a meaningfully different question than Bitquery’s survival table, though both studies count swaps — the actual exchange of one asset for another — meaning a token with zero post-launch swaps registers as dormant under both frameworks.
Token Issuance Accelerates Even as Trader Fatigue Grows Louder
Despite the bleak survival statistics, token issuance across Solana launchpads shows no sign of slowing. The launch tracker MemeFees logged at least 21,765 token launches across eight platforms on October 19 alone. Flap.sh led that single day with 10,570 launches, followed by at least 9,284 on Pump.fun and 1,707 on Pons. Seven-day averages compiled by MemeFees run to 17,726 daily launches for Pump.fun and 11,325 for Flap.sh, with the Pump.fun counts designated as lower bounds due to incomplete data collection windows.
Meanwhile, traders are beginning to voice open frustration with the dynamics driving the market. In a post on X dated October 20, an account posting as Mystral argued that “we don’t have a shortage of coins, we have a shortage of reasons to hold them,” adding that developers now expect instant volume while buyers expect instant returns. A second trader, Bishaqs, described launchpad trading as an attention market in which early buyers sell to later arrivals, and put the odds of a coin clearing the bonding curve at roughly 1 in 70. That estimate and Bitquery’s 1-in-58 graduation rate derive from different samples and definitions, so neither figure directly contradicts the other.
Why This Matters
The convergence of data from Bitquery and Jumpbit, despite their methodological differences, paints a consistent picture of an ecosystem where the overwhelming majority of tokens serve an extremely short-lived function — or none at all beyond their creation. The fact that 78% of all new Solana tokens with confirmed first trades originated on Pump.fun underscores the platform’s outsized role in shaping the broader Solana memecoin landscape. For market participants, regulators, and infrastructure builders, these figures have concrete implications: the current model generates vast volumes of activity concentrated almost entirely in launch-day windows, with almost no durable liquidity formation for the vast majority of assets. The emergence of competing launchpads such as Flap.sh — now matching or exceeding Pump.fun in single-day issuance — suggests the supply-side pressure is structural and likely to intensify, even as trader sentiment data indicates that demand-side exhaustion may be approaching a tipping point. The graduation rate — whether measured at 1 in 58 or 1 in 70 — remains the critical threshold separating tokens with any lasting market infrastructure from the majority that evaporate within hours of creation.
Frequently Asked Questions
What does the Bitquery study actually measure about Pump.fun tokens?
Bitquery’s study measures trading persistence — specifically, whether a token recorded any swap activity beyond its launch day. It does not measure price decline, holder losses, or liquidity depth. A token that traded once on launch day and never again registers as dormant in the survival table regardless of whether it crashed in price or simply attracted no further interest.
What is the graduation rate for Pump.fun tokens, and what does graduation mean?
According to Bitquery’s dataset of 8,984,141 Pump.fun tokens, approximately one in 58 tokens graduated — meaning it completed the bonding curve mechanism and moved into a PumpSwap liquidity pool, the threshold that gives a token more accessible and sustained trading infrastructure. Trader Bishaqs estimated a similar but slightly lower rate of roughly 1 in 70, though that figure comes from a different sample and methodology.
How does Pump.fun’s token survival rate compare to Meteora and Raydium LaunchLab?
Among the three platforms analyzed by Bitquery, Raydium LaunchLab had the highest share of launch-day-only tokens at 84%, followed by Pump.fun at 79% and Meteora’s Dynamic Bonding Curve at 51%. By week five, Meteora showed the highest persistence at 1.9%, compared to 1.3% for Raydium and 1.5% for Pump.fun. Bitquery cautions that differing sample structures across platforms limit the conclusions that can be drawn from these comparisons alone.




