Solana Wallets Struggle as Grass Airdrop Creates Surge

The decentralized AI training network, Grass, initiated its airdrop this morning, causing a significant influx of activity in Solana wallets.

Airdrop Claims and Wallet Issues

Grass claims to have executed one of the most extensive airdrops in history, with the GRASS token being distributed without requiring any financial investment from users. However, the demand led to technical difficulties:

• Phantom Wallet: Experienced backend outages just six minutes after the airdrop launch.
• Backpack Wallet: The CEO hinted at challenges related to claims.
• Solflare Wallet: Reported “minor degradation” but managed to scale up automatically.

Jupiter, a popular Solana swap platform, acknowledged issues affecting users on Jup.ag when utilizing third-party wallets.

RPC Protocol Performance

While the struggles of wallets might suggest issues with RPC protocols, at least two Solana RPCs appeared to maintain stability:

• Helius: CEO Mert Mumtaz confirmed their RPCs were functioning well, indicating Phantom's issues were unrelated.
• Triton One: Co-founder Brian Long noted their RPCs experienced a temporary hit but recovered quickly.

Market Reaction and Token Dynamics

Despite the wallet issues, the Solana network itself did not show signs of degraded performance during the airdrop. The price of SOL slightly decreased from $177 to $175 amidst the airdrop news.

Users initially faced challenges in claiming the GRASS tokens due to the surge in activity. Centralized exchange markets reacted positively, pushing the token price up to $1.00 on KuCoin before it experienced a sharp decline.

With a total of 100 million tokens distributed, the airdrop represented a substantial financial impact, amounting to tens of millions of dollars in new tokens.

Purpose of the GRASS Token

The GRASS token is designed to support the Grass network, developed by Wynd Labs. The network incentivizes users to share their unused internet bandwidth, which is utilized for web data scraping. This data is crucial for training AI models. Wynd Labs asserts that their method yields superior data compared to traditional web scrapers, which may face blocks or provide inaccurate information.