Parallel Inference and Batch Verification
GPU nodes accept tasks concurrently. Verifiers group tasks by Worker, model, and verification rules for batch recomputation. Users receive their results first, followed by verification and settlement.
API & Smart Contracts
Developers use the API to request inference and smart contracts to coordinate application workflows. Contracts define when calls can be made, their budgets and permissions, and what happens after a result is returned or verification is complete.
Performance & Scaling
Performance and Scaling
Each task order generates records for node participation, selection, verification, and settlement. The network performs computation off-chain, stores complete task materials in the DA layer, and submits eligible records in batches.
Task Materials in DA, Task State On-Chain
The DA layer stores inputs, outputs, and computation evidence. The blockchain records signatures, data commitments, task states, and participant obligations. When a review is needed, authorized participants retrieve the materials and check them against on-chain commitments, without repeatedly uploading the full materials to the blockchain.
Batch Submission of Task-Stage Records
Builders collect task-stage records that the protocol allows to be submitted together. The blockchain still checks each record’s signature, associated task, and prerequisites before updating the task. Batching reduces transaction overhead while preserving every individual check.
Measuring On-Chain Performance
Batching does not eliminate the blockchain’s state updates or consensus work. Further optimization and load testing are planned. Task completion rates, latency, and backlog must be measured under the same workload to make meaningful comparisons.