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Bitfury announced on December 2, 2025, that it had committed $50 million to Gonka, a decentralized network designed to coordinate distributed hardware for AI inference, training, and related workloads. The announcement also disclosed a separate $12 million purchase of GNK approved by Gonka’s community pool.
Those figures should not be conflated. The public release does not say that Bitfury purchased $50 million of GNK, nor does it disclose whether the broader commitment has closed, which instrument was used, or how the money will be deployed. Gonka’s reported scale—more than 6,000 NVIDIA H100-equivalent GPUs—is likewise a company-provided capacity comparison, not an independently audited hardware inventory.
What Bitfury actually announced
Bitfury said it would invest $50 million in Gonka as the first investment under its newly announced $1 billion initiative for emerging technologies. Gonka is described as a decentralized AI-compute network rather than a conventional cloud company.
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The investment is strategically notable because Bitfury is best known for Bitcoin infrastructure, blockchain systems, and data-center operations. Its investment portfolio now presents Gonka alongside businesses connected with advanced computing, data centers, cooling, chips, and digital-asset infrastructure. That suggests a broader interest in AI infrastructure and decentralized machine intelligence, although the announcement does not provide a detailed operational-services agreement between the companies.
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The release separately says Gonka’s community pool approved a $12 million purchase of GNK, Gonka’s native coin. The relationship between that purchase and the $50 million commitment is not explained.
What remains undisclosed
- Whether the $50 million has already been funded or is a future commitment.
- Whether it is a single transaction or a series of tranches.
- The investment instrument: equity, debt, tokens, infrastructure funding, or a combination.
- Any valuation, ownership percentage, governance rights, vesting terms, discounts, or lockups.
- How much is intended for hardware, engineering, ecosystem grants, liquidity, or operations.
Accordingly, the accurate description is that Bitfury committed to investing $50 million in Gonka. It is not accurate to say, without further documentation, that Bitfury invested $50 million in GNK or acquired part of Gonka.
What Gonka is—and is not
Gonka presents itself as a protocol for coordinating AI compute across independently operated hardware. Its documentation identifies two core participant groups:
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- Developers deploy applications and submit AI workloads.
- Hosts contribute GPUs or other suitable hardware and receive rewards for useful computation.
The blockchain is primarily a coordination, accounting, and verification layer. The actual AI computation takes place off-chain on participating hosts’ machines. Calling Gonka “a blockchain that runs AI” is therefore misleading. A more precise description is a blockchain-coordinated distributed compute network.
Gonka’s stated goal is to reduce dependence on centralized cloud and hardware providers by directing contributed capacity toward useful AI work. That is a design objective, not proof that the network currently matches hyperscale cloud services in reliability, price, privacy, or throughput.
Its own FAQ distinguishes the protocol from a conventional company and says network evolution is controlled through an on-chain self-governed mechanism rather than a foundation. That claim should be evaluated against actual voting participation, upgrade procedures, token concentration, and the distribution of host capacity—not accepted solely from the project’s description.
How Gonka’s productive Proof-of-Work model is supposed to work
Traditional Bitcoin mining uses repeated hash calculations to secure a blockchain. The calculations are intentionally difficult but do not directly produce an AI model output or other commercial computation.
Gonka describes a different approach: rewards are linked to AI-relevant computation. Its public repository refers to “Proof of Work 2.0” and a “Sprint” mechanism in which participants compete in time-limited computational races. Gonka also uses the term Proof-of-Compute for its host-reward system.
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The potential advantage is economic alignment. If a network can reward computation that is useful to developers, hardware operators are not being paid solely to perform wasteful hashes. But productive-work consensus creates a difficult verification problem. The network must establish that a host:
- Performed the requested task.
- Returned a correct or sufficiently valid result.
- Did not copy another host’s work or fabricate an answer.
- Did not collude with validators or other hosts.
- Used resources on work that has value beyond merely winning a protocol race.
Verification can be especially challenging for stochastic inference, large training jobs, privacy-sensitive workloads, and computations where checking the answer costs nearly as much as producing it. Redundant execution may improve confidence but consumes more capacity. Cheap verification may be incomplete. Penalties can deter bad behavior, but they do not automatically solve latency, model-quality, or availability problems.
For that reason, “Proof-of-Work” should not be treated as a synonym for security or efficiency. Gonka’s efficiency depends on the amount of useful work delivered after accounting for duplicate computation, scheduling, networking, storage, validation, failed jobs, and idle time.
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Gonka’s open-source repository is the relevant technical starting point for developers assessing the implementation.
What does “6,000 H100-equivalent GPUs” mean?
Bitfury and Gonka said that the network had accumulated computational resources equivalent to more than 6,000 NVIDIA H100 GPUs within roughly three months of its reported August 2025 launch.
The wording matters. “H100-equivalent” does not necessarily mean Gonka had 6,000 physical H100 cards online at the same time. The announcement does not disclose:
- A host-by-host inventory.
- The conversion method used to compare different GPUs.
- Whether the figure represents peak, theoretical, or simultaneously available capacity.
- Uptime, utilization, latency, or sustained throughput.
- Geographic distribution and redundancy.
- Independent benchmark results.
- Which models and inference workloads were supported.
The number could represent installed hardware, benchmark-normalized capacity, an aggregate theoretical total, or capacity available only for selected jobs. Without methodology, it is best reported as a company claim about equivalent computational resources, not as an audited measure of usable cloud capacity.
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Gonka’s pricing documentation describes a dynamic, model-specific system. Prices change with demand and utilization. The documentation says that at 20% utilization, the price decreases by 1% per block, while at 80% utilization, it increases by 1% per block. It also specifies a minimum floor of 1 nicoin.
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That mechanism can help avoid permanently high prices for underused models and ration scarce capacity during demand spikes. The trade-off is less predictable budgeting. A price observed during quiet conditions may not remain available when demand rises.
There is also a distinction between the protocol price and the retail price. Gonka says community brokers may add their own fees, payment methods, rate limits, and pricing. A developer comparing Gonka with AWS, Google Cloud, Azure, or a specialized GPU provider must therefore compare the final broker bill for the same model, token volume, latency target, and service guarantees—not just the on-chain compute rate.
See the project’s pricing documentation for the stated adjustment rules and query details.
GNK token economics
GNK is intended to price compute, pay for network services, incentivize hosts, and support protocol participation and governance mechanisms. Gonka’s host-rewards documentation describes a core host-incentive allocation of 680 million GNK, or 68% of total supply. Rewards are distributed according to hosts’ Proof-of-Compute weight, with an approximately four-year halving pattern.
The project’s tokenomics documentation describes inference fees using this formula:
Final Fee = (Prompt Tokens + Actual Completion Tokens) × Units of Compute per Token × Unit of Compute Price
That formula makes model choice important: two models processing the same number of tokens may consume different amounts of compute. The unit price is also dynamic, and a broker can add another layer of charges.
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Gonka’s FAQ identifies WGNK as the official Ethereum representation of GNK. It also said native GNK was not listed on a centralized exchange at the time of that documentation snapshot. Listings, bridges, liquidity, and contract arrangements can change, so readers should verify current information directly through the project’s FAQ and official channels before transferring funds.
Who created Gonka?
According to Bitfury’s announcement, Gonka was originally incubated by Product Science, a U.S.-based software company founded by Anna, David, Daniil, and Maria Liberman. The release also names Coatue Management, Slow Ventures, and K5 as backers.
That history should be separated from the network’s current structure:
- Product Science is identified as the original incubator.
- Gonka is presented as a protocol and network.
- The GitHub repository and community represent open-source development activity.
- Bitfury is a strategic investor announced after launch.
- On-chain governance is the project’s claimed control mechanism.
Formal decentralization and practical decentralization are different questions. A network may have permissionless software while a small group controls most voting power, gateways, token supply, or compute capacity.
What Bitfury could add
Bitfury’s background in blockchain infrastructure, hardware deployment, data centers, and advanced computing could be relevant to Gonka’s stated ambitions. Potential contributions include sourcing and deploying hardware, arranging data-center capacity, improving operational infrastructure, supporting engineering, and bringing institutional credibility.
These are reasonable strategic possibilities, not disclosed deal terms. The public announcement confirms the capital commitment and Bitfury’s stated rationale, but not a specific hardware rollout, service-level agreement, or engineering plan.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Who might use Gonka?
Potentially suitable use cases
- Developers experimenting with open or non-sensitive workloads.
- Researchers seeking flexible inference capacity.
- Projects willing to tolerate evolving APIs, pricing, and network behavior.
- GPU owners with idle hardware and the technical ability to operate hosts.
Cases requiring caution
Gonka should not automatically be treated as a replacement for an enterprise cloud deployment. Buyers requiring guaranteed latency, formal support, predictable fiat billing, strict data residency, compliance certifications, confidentiality, indemnification, or a contractual SLA need evidence that the specific Gonka access path provides those controls.
Distributed hardware can vary in GPU model, VRAM, drivers, interconnects, bandwidth, cooling, uptime, and security posture. Aggregate capacity does not establish consistent service quality.
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Key risks that the investment does not solve
Verification and reliability
The central technical question remains whether useful AI work can be verified cheaply and securely at scale. A network can have substantial nominal capacity while still experiencing failed jobs, inconsistent results, bottlenecks, or insufficient redundancy.
Privacy
Decentralization does not automatically improve confidentiality. Developers should ask whether hosts can see prompts or inputs, whether data is encrypted during processing, whether model weights can be extracted, whether operators can log requests, and whether confidential-computing hardware or data-residency controls are available.
Economic volatility
Hosts face token-price risk and uncertain utilization. Users face dynamic pricing and possible broker markups. Wallet, bridge, custody, tax, and regulatory issues may also matter depending on jurisdiction.
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Actual host concentration, voting participation, investor influence, gateway control, and upgrade authority matter more than the label “self-governed.” These metrics should be examined before making a strong decentralization claim.
Protocol maturity
Gonka’s network updates document protocol changes during 2026, including changes to inference routing and Proof-of-Compute and “devshard” infrastructure. That is evidence of active development, but also means APIs, economics, and operating assumptions may continue to change.
What readers should demand before treating Gonka as cloud infrastructure
- Capacity methodology: Explain how H100-equivalent capacity is calculated and publish simultaneous availability, uptime, utilization, and throughput.
- Service metrics: Report latency distributions, failure rates, model coverage, geographic redundancy, and recovery procedures.
- Verification details: Describe task assignment, redundancy, result checking, dispute handling, and penalties for dishonest hosts.
- Transaction disclosure: Clarify the $50 million instrument, closing status, valuation, ownership, governance rights, and the separate $12 million GNK purchase.
- Token terms: Publish allocations, vesting or lockups, reward schedules, liquidity arrangements, and protocol-change procedures.
- Privacy and security: Document host visibility, encryption, logging, model protection, audits, and data-residency options.
- Commercial terms: Show the final broker price, fees, rate limits, payment options, support terms, and any SLA.
How the announcement should be interpreted
Bitfury’s commitment is meaningful as a validation signal and a possible catalyst for more hardware, engineering, and ecosystem activity. It indicates that an established blockchain-infrastructure investor sees potential in Gonka’s attempt to connect decentralized hardware with AI workloads.
It is not, by itself, evidence that Gonka has solved the hardest problems in decentralized AI: verifiable useful computation, reliable production service, privacy, predictable pricing, sustainable host economics, and genuine decentralization. The most defensible conclusion is that Gonka is an emerging, actively evolving compute protocol with an ambitious design and substantial announced backing—not yet proven to be a production-scale replacement for centralized AI clouds.
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