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Bitwise Launches First US Spot NEAR ETF (NRR) With Staking Rewards

Saravana Kumar Mahendran by Saravana Kumar Mahendran
October 1, 2026
in Market Updates
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Bitwise Launches First US Spot NEAR ETF (NRR) With Staking Rewards
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  • Bitwise launched NRR, the first U.S. spot NEAR ETF, on NYSE Arca on September 29, 2026, with a 0.75% management fee
  • The fund passes through staking rewards to shareholders, with an annualized yield of approximately 5.3% as of September 25, 2026
  • Bitwise manages roughly $9 billion in client assets as of June 30, 2026, and frames NRR as exposure to both artificial intelligence and crypto through NEAR’s AI-focused roadmap

Bitwise Asset Management announced in a release distributed on PR Newswire at 9:00 a.m. ET on September 29, 2026 that the Bitwise NEAR ETF, trading under the ticker NRR, has launched on NYSE Arca as the first U.S. spot NEAR exchange-traded product.

The fund carries a 0.75% management fee and is structured to pass staking rewards through to shareholders rather than keeping the yield for the fund manager. Bitwise said the fund’s annualized staking yield stood at approximately 5.3% as of September 25, 2026, giving investors exposure to both NEAR’s token price and its underlying staking economics through a single, exchange-listed security.

“NEAR sits at the intersection of two of the biggest trends in technology: AI and crypto,” said Bitwise chief investment officer Matt Hougan in the release. NEAR Protocol co-founder Illia Polosukhin added that “private and verifiable AI, blockchain-based security, and universal liquidity via Intents are working together to power the agent economy,” framing the token’s value proposition around its bet on autonomous AI agents transacting onchain. Bitwise chief executive Hunter Horsley said the firm expects a future “in which AI agents increasingly act on our behalf, coordinate with one another, and participate in the economy,” positioning NRR as an early way for traditional investors to gain exposure to that trend.

Bitwise managed roughly $9 billion in client assets as of June 30, 2026, according to the release, making it one of the larger dedicated crypto asset managers now competing to bring single-asset altcoin exposure to U.S. exchanges. NRR adds to a growing lineup of spot crypto ETFs beyond bitcoin and ether that asset managers have pushed to list over the past year, wagering that investor appetite extends to smaller, more specialized tokens with distinct narratives, such as NEAR’s focus on AI infrastructure.

Launching a staking-enabled ETF also tests how comfortable U.S. regulators and exchanges have become with funds that generate and distribute yield from proof-of-stake consensus, a structure that was effectively unavailable to American investors through regulated products until relatively recently. Whether NRR draws meaningful inflows will likely depend on how directly investors buy into the pairing of NEAR’s staking yield with its AI-agent narrative, rather than simply treating it as another way to speculate on token price.

Disclaimer: Cryip's content is strictly for educational and informational purposes and does not constitute financial, legal, or investment advice. Cryptocurrency involves significant risk, and readers assume full responsibility for their own financial decisions. Asset references are never endorsements.

To make complex crypto topics accessible to readers at all experience levels, our team uses AI tools strictly to refine language, correct grammar, and simplify terminology. AI is never used to draft facts, source information, or form conclusions. Every article is fact-checked and approved by a human editor before publication. Read our full AI Use & Content Policy.

Saravana Kumar Mahendran

Saravana Kumar Mahendran

Saravana Kumar Mahendran is a crypto security analyst and blockchain researcher at Cryip, focusing on DeFi protocol exploits, Web3 security systems, and on-chain investigation. His research applies OSINT and fact-checking methodology to security incidents, drawing on certifications in cybersecurity and data analytics (LinkedIn Learning), and DeFi deep-dive training (Binance Academy). His work has been cited by Sherlock, Rekt.news, and Halborn Security.

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