Halo is a decentralized AI inference platform developed within the Warden Protocol ecosystem. The project creates a peer-to-peer marketplace for computing resources, where hardware owners can run AI models and process user requests, with payments settled directly through blockchain infrastructure. Halo operates at the intersection of artificial intelligence and DePIN: instead of relying on centralized cloud providers, computing workloads are distributed among independent operators. At its initial stage, payments within the network are handled in USDC on Base, while users can access models without traditional accounts or API keys.
Contents:
- What Is Halo and How Does Decentralized AI Inference Work?
- Halo's DePIN Architecture and Compute Operators
- AI Models, Payments, and Warden Protocol Infrastructure
- Halo vs. Centralized AI Inference Platforms
- Halo Economics, Scalability, and Risks
1. What Is Halo and How Does Decentralized AI Inference Work?
Halo was introduced in 2026 as a permissionless network for peer-to-peer AI inference. Inference is the process of using an already trained model to process a request and generate an output. This stage powers chatbots, AI agents, content generators, and other applications based on large language models.
In a traditional architecture, developers typically access a centralized AI provider through an API. Computations are performed in the provider's data centers, while the company determines which models are available, pricing, usage limits, and access conditions. Halo proposes a different structure: models can be served by independent operators providing their own computing resources.
A user selects an available model and submits a request through Halo. The request is then routed to an operator capable of performing the required computation. Users pay for the inference they actually consume, removing the need to purchase dedicated hardware or continuously rent a separate GPU server.
The project emerged from the Warden Protocol ecosystem, which focuses on infrastructure for AI and autonomous agents. In 2026, Halo became one of the key development areas of the Warden Foundation. Within this architecture, Halo primarily provides distributed access to models and computing resources, while the broader Warden stack includes tools for identity, verification, and interactions between AI agents.
2. Halo's DePIN Architecture and Compute Operators
Halo can be classified as an AI DePIN project, although its physical infrastructure differs from networks built around sensors, wireless access points, or decentralized storage. In this case, the physical resource is computing hardware capable of performing AI inference, including personal computers, GPU systems, servers, and other compatible devices.
Operators connect their hardware to the network and provide computing capacity for running models. This approach makes it possible to aggregate distributed resources owned by different participants instead of concentrating the entire infrastructure in a small number of centralized data centers.
- AI models — the software layer that operators make available to network users.
- Compute operators — participants providing hardware for AI inference.
- Peer-to-peer marketplace — connects demand for AI computing with available resource providers.
- On-chain payments — used to settle transactions between consumers and operators.
- Permissionless access — enables participation without relying on a single centralized AI provider.
Hardware requirements depend on the model being used. Smaller models can run on consumer devices, while large LLMs require significantly more memory and computing power. A decentralized marketplace therefore needs to account for differences between operators in terms of performance, cost, and resource availability.
According to the Warden Foundation, by the end of July 2026 Halo had already processed more than 7 billion AI tokens and supported over 160 models. The project also states that different types of hardware can participate as operators, ranging from Mac Minis and gaming PCs to GPU clusters. These figures indicate network usage but do not by themselves determine its economic sustainability or the quality of individual providers.
3. AI Models, Payments, and Warden Protocol Infrastructure
One of Halo's features is an access model that does not require a traditional API account. Users can interact with the inference network through Web3 infrastructure and pay for requests with cryptocurrency. At launch, Halo uses Base as its primary payment network, with USDC serving as the settlement asset.
Using a stablecoin helps separate computing costs from the volatility of a native crypto asset. Users pay for inference with an asset designed to track the U.S. dollar, while operators receive economic compensation for the resources they provide. This mechanism resembles the pay-per-use model of cloud services, but settlement takes place through public blockchain infrastructure.
Halo is closely connected to Warden's broader architecture. Warden Protocol was designed as infrastructure for the agentic economy — an environment where software-based AI agents can interact with services and blockchains. Such an economy requires not only access to models but also mechanisms for verifying results, identifying participants, managing permissions, and executing transactions.
Distributed inference can serve more than individual end users. Developers can integrate computing resources into AI applications and agents without being tied to a single model provider. However, the practical competitiveness of this approach depends on API and interface stability, request latency, availability of specific models, and computing costs compared with traditional cloud platforms.
4. Halo vs. Centralized AI Inference Platforms
Halo's main distinction is not the development of proprietary foundation AI models, but the way access to computing resources is organized. Centralized platforms control both hardware and the software layer, while Halo creates a marketplace connecting independent resource providers with users.
| Parameter | Halo | Centralized AI API | Traditional DePIN |
|---|---|---|---|
| Primary Resource | AI inference and computing | Cloud-based AI computing | Physical infrastructure |
| Providers | Independent operators | Centralized company | Distributed operators |
| AI Models | Multiple models | Determined by the provider | Not necessarily a core component |
| Payments | USDC via Base | Fiat or centralized billing | Depends on the network |
| Access | Permissionless model | Account and API key | Depends on the project |
| Main Risks | Compute quality, operators, and blockchain infrastructure | Centralization and provider dependency | Hardware and incentive economics |
Decentralization can potentially expand the geographic distribution of computing resource providers. Hardware that would otherwise remain underutilized can be connected to the network. This is particularly relevant to AI, as the growing number of models and applications continues to increase demand for GPUs and other computing resources.
However, distributed architecture introduces its own challenges. A centralized data center can standardize hardware, networking, and service quality. In a DePIN system, operator performance can vary, making latency, node availability, computation accuracy, and the ability to reroute requests during failures important considerations.
5. Halo Economics, Scalability, and Risks
Halo's economy is built around the AI inference market: users pay to process requests, while operators receive compensation for providing computing resources. Unlike DePIN models that rely primarily on token emissions, Halo depends on real demand for AI computing services.
The project is connected to Warden Protocol and the WARD token, but Halo is primarily being developed as a computing network. User payments are made in USDC through Base, meaning that the economics of the inference service should be evaluated separately from the market value of related crypto assets.
The main technological risks include instability of distributed nodes, differences in hardware performance, and the need to verify computation results. Speed and availability are also critical for AI services: decentralized infrastructure must compete with centralized cloud platforms on both parameters.
Data privacy is another important factor because user requests are processed by compute nodes. Additional risks exist at the smart contract, payment infrastructure, blockchain, and operator software levels. Overall, Halo combines AI and DePIN within an open marketplace for computing resources. Its future development will depend on the number of operators and available models, inference costs and quality, developer demand, and the network's ability to compete with centralized AI providers.
