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DCG-Backed Yuma Introduces Fund to Give Institutions Bittensor Exposure



Digital Currency Group-backed investment firm Yuma has launched the Yuma Total Market Fund, a pooled product designed to give institutional investors diversified exposure to the Bittensor ecosystem—without requiring them to pick individual subnet tokens.


Announced on Thursday, the fund is structured to provide exposure to Bittensor’s native TAO token alongside a basket of AI-focused subnets. Yuma says the aim is to package participation in Bittensor’s decentralized AI infrastructure economy into a single vehicle, with seed capital provided by an undisclosed anchor investor.



Key takeaways



  • Yuma’s new fund targets broad exposure to Bittensor via TAO plus a basket of AI subnet assets in one pooled strategy.

  • The firm positions the approach as simpler than selecting and managing individual subnet tokens directly.

  • Network “subnet value” figures vary materially depending on the tracker used—Yuma cites $900M+ across 128 subnets, while Taostats points to roughly $300M.

  • Institutional interest in Bittensor-linked assets has been rising, reflected in Grayscale’s evolving TAO weighting and filings for TAO exchange-traded products.

  • Renewed attention to decentralized AI follows US Commerce Department actions impacting access to Anthropic models, underscoring the debate over reliance on centralized providers.



A fund built around Bittensor’s subnet economy


Bittensor is a decentralized network for building AI infrastructure and applications, operating through specialized subnets. These subnets focus on different areas such as compute, marketplaces, and identity. Rather than betting solely on the performance of TAO as a single token, Yuma’s strategy blends exposure to TAO with additional subnet-related assets.


According to Yuma, Bittensor’s 128 subnets collectively represent more than $900 million in combined value. However, data from network tracker Taostats suggests a lower combined subnet value—closer to $300 million. For investors, this gap matters because the “size” of the subnet economy can be measured differently depending on the methodology behind network trackers, and those assumptions influence how meaningful “diversification across subnets” really is.


Yuma did not disclose the anchor investor that provided seed capital. Still, the launch signals a shift in how asset managers are structuring access to decentralized AI systems: instead of treating Bittensor as a single-token theme, they are increasingly packaging it as an ecosystem.



How institutional allocations are changing for TAO


Institutional exposure to Bittensor-linked assets has broadened alongside the network’s expanding subnet economy, and TAO allocations within established funds offer a window into how managers are rebalancing their decentralized AI theses.


In April, Grayscale increased TAO’s weighting in its Grayscale Decentralized AI Fund to 43% during the fund’s quarterly rebalance. Since then, TAO’s allocation has fallen to about 20%, while Near Protocol’s NEAR has become the largest holding at roughly 44%.


That evolution highlights a familiar dynamic in crypto asset management: even when a thesis is “decentralized AI,” the portfolio can still rotate as managers weigh relative opportunities across tokens they view as part of the same broader category. For readers, it suggests that TAO may remain central to decentralized AI exposure, but it is not immune to shifting portfolio construction as other ecosystem players gain weight.



ETF momentum: filings for TAO exposure


Beyond private funds, the push to bring TAO exposure into more traditional investment wrappers is also accelerating. Asset managers have been filing with US regulators to create exchange-traded products tied to Bittensor.


In April, Bitwise filed for a TAO Strategy ETF with the US Securities and Exchange Commission (SEC). Grayscale, meanwhile, submitted an amended registration statement aimed at converting its existing Bittensor Trust into a spot TAO exchange-traded fund that would be listed on NYSE Arca, if approved.


These filings reflect growing demand from investors who want exposure to decentralized AI through regulated market infrastructure. If regulators approve spot TAO structures, it could reduce friction for institutional allocators who prefer standardized instruments over bespoke crypto holdings.



Why decentralized AI is back in focus


The interest in Bittensor’s model is occurring amid renewed scrutiny of centralized AI access. The case for decentralized AI—where AI infrastructure and computing are distributed across blockchain-based networks rather than relying on a single provider—has gained traction after the US Commerce Department suspended public access to Anthropic’s Fable 5 and Mythos 5 models over national security and export control concerns.


Grayscale head of research Zach Pandl argued that the restrictions underscored the risks of centralized control of AI. According to Pandl, investors may seek alternatives such as Bittensor and its TAO token as they look for ways to avoid single-provider chokepoints.


While the restrictions initially tightened, the situation appears to be easing. The Commerce Department restored access to Mythos 5 on Friday, and Axios reported Saturday that the Trump administration is expected to allow Anthropic to resume public access to Fable 5 as soon as next week.


Even if access returns quickly, the episode has already reframed parts of the conversation around decentralized AI. For market participants, it raises a practical question: are investors buying “decentralized AI” as a speculative crypto theme, or as a hedge against policy-driven disruptions that can affect availability and control of AI models?



What to watch next


With Yuma’s fund now live and multiple managers pursuing TAO-linked ETF pathways, the next signal to monitor is how these products structure their exposure to TAO versus subnet baskets—and whether regulatory outcomes for spot listings translate into broader institutional demand for Bittensor ecosystem exposure.



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