Vanna Labs
  • Introduction
    • 👋Welcome
    • ✨Summary
  • Vision
    • 🏪The AI One-Stop-Shop
      • AI Models on Vanna
      • Applied ML on Vanna
    • 🤝Interoperability
    • ✅Computational Verifiability
    • 🌐Decentralization
    • 🛡️Censorship Resistance
  • Vanna Network
    • 🏗️Architecture
      • Data Preprocessing
      • Parallelized Inference Pre-Execution (PIPE)
      • Validation-Computation Separation (VCS)
      • Cryptoeconomic Security
      • Modular Design
    • ⚙️Inference Modes
      • Vanilla Inference
      • zkML Inference
      • zkFP Inference
      • opML Inference
      • TEE Inference
    • 💿Data Storage
      • Model Storage
      • Data Availability
    • 💻Portal
  • Build
    • 🛠️Getting started
      • Networks
      • Faucets
      • Model Storage
    • 💻Building dApps
      • Data Preprocessing
      • Inference API
      • Inference Example
    • 💾Models
      • Supported LLMs
  • 🔗Links
  • Key Concepts
    • 🧠AI x Blockchain
    • 📜Optimistic Rollups
    • 💾Data Availability
    • ⚡zkML
    • ☀️opML
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  1. Vanna Network

Inference Modes

Types of Inference on the Vanna Network

Vanna supports a variety of flavors of inference to suit all sorts of use-cases depending on demands for speed, cost, verifiability, and security.

  • Vanilla Inference

    • Fast execution of inference through leveraging GPU hardware acceleration and transaction parallelization

  • zkML Inference

    • Inference where the inference node also subsequently generates a zkML proof with EZKL. The proof is then validated by validator nodes on the Vanna Network for an absolute guarantee of security.

  • zkFP Inference

    • Inference where the inference computation is assumed to be honest, but makes the transaction available for challenge. If challenged, the challenger puts up a stake and the inference node must provide a zkML proof proving the result.

  • opML Inference

    • Inference where the inference computation is assumed to be honest, but makes the transaction available for challenge. If challenged, the challenger puts up a stake and a bisection verification game is played to see whether the inference node was honest.

  • TEE Inference

    • Run a private enclave node with the model stored locally, so the model weights remain private. Inference requests for the model are routed to that node, with a zkML proof subsequently generated and verified by the Vanna Network.

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Last updated 1 year ago

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