The Sui network has officially introduced gasless stablecoin transfers, a technical update aimed at removing one of the primary friction points for digital payments. The feature allows users to send stablecoins without holding the network’s native SUI token to cover transaction fees.

Sending a stablecoin:

Other chains: transfer → gas fee → wait → wait more → gas spike → retry ❌

Sui: transfer → no gas → done ✅

— Sui (@SuiNetwork) July 14, 2026

A demonstration of the new flow was shared by the @SuiNetwork official account on X, highlighting a comparison between Sui’s streamlined process and the multi-step “retry” cycles often required on other blockchains when gas fees fluctuate or are insufficient. The update is part of a broader infrastructure push to position the network as a viable alternative for high-volume payment applications.

Infrastructure for the “Payments Network” Narrative

The transition to gasless transfers addresses a long-standing barrier in the stablecoin market: the requirement for users to manage secondary asset balances just to move liquidity. By abstracting these costs, Sui aims to provide an experience closer to traditional fintech applications while maintaining on-chain settlement.

According to the Sui Foundation in an official blog post, this capability is a core component of the “Sui Stack,” a developer-focused rollout intended to evolve the Layer-1 into a more comprehensive platform. The network’s ability to process transactions in parallel serves as the underlying technical foundation for maintaining low latency during these transfers.

Market Response and Observed Activity

While the feature targets retail and payment adoption, early data suggests significant participation from automated systems. Secondary reports indicate that within the first five days of the launch, transfer volumes reached approximately $65 billion. Analysts have noted that a portion of this initial activity likely originated from arbitrage bots testing the network’s high throughput capabilities under the new fee structure.

The broader ecosystem has shown steady liquidity growth alongside these technical updates. Total Value Locked (TVL) on the network has trended upward, and stablecoin capitalization—primarily led by USDC—has recently reached approximately $460 million. This liquidity provides the necessary backbone for the gasless feature to function across decentralized finance (DeFi) protocols and peer-to-peer transfers.

Despite the official rollout and the confirmed functionality of the gasless flow, long-term adoption metrics remain pending. The available data captures an initial surge in activity, but it remains unclear how much of this volume will translate into sustained organic usage once the novelty and early testing phases conclude. For now, the development marks a shift in Sui’s strategy to compete for the stablecoin payment sector by prioritizing user experience over traditional fee models.

The post Sui Implements Gasless Stablecoin Transfers to Streamline Payments appeared first on The Cryptocurrency Post.

NEAR Protocol has detailed a new technical approach to AI execution, confirming that NEAR AI now utilizes secure hardware enclaves to provide verifiable private inference. The system is designed to return hardware-signed proofs that verify the specific model used, the data processed, and the execution itself, addressing growing concerns over data sovereignty and the limitations of closed AI models.

The development shifts the trust model from contractual agreements to cryptographic and hardware-level certainty. By running AI agents within a user-owned stack, NEAR aims to provide a structural alternative to centralized AI providers, particularly in light of increasing export controls and data privacy restrictions.

Secure Enclaves and Hardware Proofs

At the core of this update is the use of Trusted Execution Environments (TEEs), such as Intel TDX and confidential GPUs. According to official NEAR AI documentation, these secure enclaves allow inference to run in an isolated environment where memory is encrypted at the CPU level. This prevents host operators, hypervisors, or unauthorized third parties from accessing the data being processed.

AI sovereignty wasn’t a hot topic, but NEAR’s been building for it for years. Then export bans and government equity stakes changed the conversation fast.

NEAR AI already runs a user-owned stack, and IronClaw secures the agent layer. 

Sovereignty you can verify. https://t.co/69SHawbBQA pic.twitter.com/TbVtk7PNBY

— NEAR Protocol (@NEARProtocol) July 9, 2026

The system generates a cryptographic “attestation” or hardware-signed certificate. This proof allows users or third parties to verify that the workload ran exactly as intended without being modified. The NEAR Protocol official account noted that the IronClaw security layer is used to protect the agent level, ensuring that users maintain sovereignty over their data and model interactions.

Addressing Data Sovereignty

The move toward verifiable inference comes as a response to the “closed” nature of frontier AI models. In typical cloud-based AI interactions, users must rely on the provider’s contractual promise that data is not being stored or used for training. NEAR’s implementation replaces this reliance on trust with “structural assurances,” where the silicon itself proves the security of the environment.

This approach is particularly relevant for:

• Export Controls: Providing verifiable proof of hardware and execution locations.
• Sensitive Workloads: Allowing institutions to run models on rented cloud compute without exposing proprietary data to the cloud provider.
• Model Integrity: Ensuring that the specific version of an AI model requested is the one actually performing the task.

Status and Integration

While the technical framework for private inference and hardware attestation is now officially documented and confirmed, specific adoption metrics remain pending. The available sources do not yet provide data on total usage numbers or a comprehensive list of third-party integrations launched within the last 48 hours. The current focus remains on the deployment of human-owned AI stacks that leverage these secure hardware proofs to bypass centralized bottlenecks.

The post NEAR Protocol Confirms Verifiable Private Inference for AI appeared first on The Cryptocurrency Post.