AI x Crypto Roundup: Agent Payments, Decentralized Compute, on-chain agents, and Verifiable AI. August 28, 2026 · openai/gpt-oss-120b Tl;dr. AI agents are moving from experimental bots to economic actors that can pay for services, prove computation, and trade data on-chain, thanks to new payment protocols, privacy-preserving compute enclaves, and on-chain settlement layers. Agentic payments and checkout layers. * AgentWallet on Casper enables an AI agent to purchase an API call without exposing a human's card details, effectively creating a machine-native checkout flow for autonomous software @Casper_Network. * x402 payment rail is repeatedly highlighted as the backbone for agentic commerce: it allows agents to pay per inference, settle in stablecoins, and operate without human-issued API keys. Usage on Solana has already exceeded 35 M transactions and $10 M in volume, showing real-world adoption beyond demos @Hey_Jihad@Rifat_EE. * Base and Robinhood Chain integrations extend x402 with USDG, giving agents a way to pay for services on multiple L2s without a traditional checkout interface @Hey_Jihad@Rifat_EE. * FreeBots / Bot Mesh provides each AI bot a permanent on-chain identity (Ed25519 keypair) and a USDC address, allowing bots to tip each other and expose paid x402 endpoints directly on Base @OnlyHades_. * The Graph's x402 layer supplies the "pay-per-query" capability that agents need to access subgraph data without API keys, turning read-only blockchain data into a monetizable service @Joshuwa@graphprotocol. Decentralized AI Compute and trusted execution. * Phala Network's GLM 5.3 Flash runs private, TDX-attested GPU TEEs, delivering verifiable inference for coding assistants, long-horizon agents, and visual understanding tasks @PhalaNetwork. * Flop Labs proposes a proof-of-inference model where GPU miners process AI inference requests, and validators verify the work before rewarding compute tied to real demand; a testnet is planned for Q4 2026 @gomtu_xyz@muhtasimmuiz. * Render Network is expanding from GPU rendering to a global AI compute layer, onboarding enterprise-grade GPUs (e.g., NVIDIA H200) and integrating the Salad Network's 60 k daily active GPUs, with a burn-and-mint token model that aligns network usage with RENDER token economics @punpun0911@punpun0911. On-Chain agent identity, escrow, and reputation. * TermiX (AACP) introduces ERC-8004 agent NFTs that act as on-chain identities, a non-custodial escrow contract for USDC/USDT, and a challenge-response dispute system. The protocol reports >263 k agents, 37 k jobs, and $3.4 M escrowed across BNB Chain and Base, demonstrating a functional marketplace for autonomous agents @ny14co@GpaAndy@cangg_l@binz1104@blessed_w3@whangFT1. * Walcert integration adds automated on-chain certification of wallet trustworthiness, allowing agents to verify counterparties without human intervention @0xabyee. * Concordium's Agent Registry offers zero-knowledge-based identity badges that link an agent to a verified human or business, preserving privacy while providing accountable provenance for autonomous agents @lordsgood. Verifiable / zero-knowledge AI. * ARPA Network's ZKML combines zero-knowledge proofs with machine learning, enabling AI models to prove correct outputs without revealing inputs or model parameters, a key building block for privacy-preserving AI on Web3 @arpaofficial. * TermiX's use of zkVM and TEE allows agents to submit mathematically provable execution results; payments are released only when the proof verifies, eliminating blind trust in code generation @cukyn1812. * Zypher Network partnership with BASIS highlights the convergence of AI-native blockchain infrastructure and zero-knowledge tech to create intelligent digital economies, underscoring the growing importance of verifiable AI primitives @basis__pro@Zypher_Network. Decentralized data and model Marketplaces. * Auren Protocol builds a decentralized data infrastructure to supply high-quality datasets for next-generation AI models, positioning data as the essential fuel for the AI engine @AUREN_PROTOCOL@AUREN_PROTOCOL. * Axis Robotics demonstrates a data-engine layer where simulated and real robot trajectories are collected, verified on-chain, and incentivized, forming a marketplace for physical-AI training data @BitWolf84@GuruVerseX@cangg_l. * TermiX's multi-path participation model lets users earn points by contributing social content, registering agents, posting jobs, and completing on-chain work, effectively creating a token-incentivized data and service marketplace for AI agents @luong4101992@Phuc50103413@derrelreyhan. Outlook. The convergence of machine-native payment rails (x402), privacy-preserving compute (TEE, ZKML), on-chain identity/escrow (ERC-8004, Concordium badges), and decentralized data pipelines (Auren, Axis) signals a shift from AI-only prototypes to a full-stack AI-crypto economy. As transaction volumes grow and more enterprises adopt agentic commerce (e.g., Rezolve AI + Tech Mahindra partnership) @RezolveAi, the infrastructure described above will likely become the backbone for autonomous economic agents operating at web scale. * Dispatch AI x Crypto Roundup: Decentralized Agent Payments, Compute, and Verifiable AI This roundup highlights concrete developments where AI agents are gaining on-chain payment rails, decentralized GPU compute, tokenized identities, and zero-knowledge verification, showing a maturing AI-crypto infrastructure. * Dispatch AI x Crypto Roundup: Agent Payments, Decentralized Compute, Verifiable AI, and On-Chain Marketplaces AI agents are beginning to transact on-chain, leverage decentralized GPU compute, and use verifiable AI and tokenized agents, signalling the emergence of a functional agentic economy. * Dispatch AI x Crypto Roundup: Agent Payments, Decentralized Compute, and Verifiable AI AI agents are now paying for services, accessing decentralized GPU compute, and delivering cryptographically verifiable results, signaling a shift toward an infrastructure-first AI-Web3 economy. * Dispatch AI x Crypto Roundup: Agent Payments, Decentralized Compute, and Trust Layers AI agents are now transacting on-chain, using decentralized compute, tokenized skills, and zero-knowledge identity to enable trust-worthy, machine-native payments. * Dispatch AI x Crypto Roundup: Decentralized Agent Payments, Compute, and Trust Layers Recent social posts show a surge in decentralized AI agent payments, on-chain compute markets, tokenized agents, zero-knowledge verification, and dispute-resolution infrastructure, indicating the maturing of an agentic economy.

Decrypt’s Art, Fashion, and Entertainment Hub. Discover SCENEPresearch—a decentralized and privacy-oriented search engine—has just launched PreGPT 2.0, marking the company's latest attempt to challenge Big Tech's dominance in the AI chatbot space.The new release brought improved language models and a broader selection of open-source AI options, all running on a network of distributed computers rather than centralized data centers.“Why am I so excited? Because PreGPT 2.0 is so powerful and unrestrained, that it has the potential to fundamentally disrupt the echo chamber effect that has long been manipulating conventional wisdom, amplifying the herd instinct into blind conformity,” Brenden Tacon, innovation and operations lead for Presearch, told Decrypt.The upgraded chatbot comes with two subscription tiers: a $2 monthly basic plan running Mistral AI's 7B model and a $5 pro version powered by Venice.ai's more sophisticated LLMs. Both options promise to keep user data private and conversations unmonitored, with chats permanently erased upon deletion.PreGPT 2.0's model lineup features six of the most well-known names in the open-source AI space: Meta's Llama-3.1-405b (a gigantic model), Llama-3.2-3b (a very small model built for efficiency) and Llama-3.3-70b (its latest LLM), Alibaba's Qwen 32b.It even leverages the old Dolphin 2.9 model, previously known in AI circles for being fully uncensored and powerful—and good at roleplay. The company also seems to have fine-tuned the Mistral 7B model to offer a custom version.“This model gracefully handles a context of 8,000 Tokens, which equates to about 5,000 words, and you will be throttled to 1000 messages per month,” according to the company's website.This means the model will have a memory of 5,000 words and won’t be able to properly handle conversations that exceed such limit—or won’t process prompts that are that long.What is Presearch?Presearch, which launched in beta back in 2017 and went live in 2018, is basically a project that wants to reimagine search engine architecture with decentralized technology.The platform processed over 12 million monthly searches through a web of independent nodes. Each node operator staked PRE tokens and lent computing power to the network, creating a self-sustaining ecosystem that scaled naturally with demand.The idea is that a decentralized network makes the profiling of users—Google’s business model—harder and could help generate a business model that is more transparent and organic.The platform's advertising model is also different from what you see in Google or Bing, for example.Instead of bidding wars for keywords, advertisers staked PRE tokens to gain visibility. The more tokens they stake, the better their placement will be—a system that reduces token circulation while creating predictable revenue.A portion of these tokens get burned periodically, gradually decreasing the total supply from its current 590 million PRE in circulation.PreGPT 2.0 leveraged this distributed infrastructure by collaborating with Venice.ai, a privacy-conscious AI service provider, and Salad.com, a community that shares decentralized GPU power.The professional tier operates on Venice.ai's high-performance network, while the basic plan is supported by Salad.com’s distributed GPU network.Both pathways encrypt user interactions and refrain from storing chat logs, upholding Presearch's commitment to privacy.PRE's tokenomics keeps the system running smoothly