PERP.WIKI

Pyth Network vs Silo Finance

Hyperliquid ecosystem comparison · Oracles

Ecosystem Pick
Different Focus Areas

Quick Take

Pyth Network High-fidelity oracle delivering real-world market data to Hyperliquid on Multi-Layer, while Silo Finance Isolated lending markets ensuring risk containment for any token on HyperEVM on Multi-Layer. They serve different niches in the Hyperliquid ecosystem.

Based on public data for Pyth Network and Silo Finance. Key differentiators: layer deployment, fee structure, liquidity depth, and community adoption. Last reviewed: Mar 2026.

Overview

Pyth Network logo

Pyth Network

Pyth Network is a high-fidelity, low-latency oracle that delivers real-world market data to smart contracts on over 50 blockchains including Hyperliquid. Hyperliquid integrates Pyth's price feeds to power its perpetual and spot markets, ensuring reliable mark prices and funding rates. Pyth uses a pull-model where publishers—including major trading firms like Jump Trading and Jane Street—push prices on-chain only when consumed, dramatically reducing costs. With sub-second update frequencies and over 500 price feeds covering crypto, equities, FX, and commodities, Pyth is one of the most widely used oracles across the HyperEVM ecosystem. Its decentralized network of first-party data sources ensures data accuracy and tamper-resistance, making it a critical infrastructure layer for DeFi protocols building on Hyperliquid that require accurate, real-time pricing for collateral valuation, liquidation triggers, and perpetual mark prices.

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Silo Finance logo

Silo Finance

Silo Finance is an isolated lending market protocol where each asset gets its own lending silo, ensuring that a compromise in one market cannot cascade to others. By pairing each asset with a bridge asset (ETH or stablecoins), Silo achieves risk isolation while maintaining capital efficiency for borrowers. This architecture is particularly valuable on HyperEVM where newer Hyperliquid spot tokens carry varying risk profiles. Silo v2 introduces permissionless market creation with configurable interest rate models and liquidation mechanisms, enabling any project to deploy a lending market for their token on Hyperliquid. The protocol's battle-tested security model and isolation-first design make it attractive for long-tail asset markets that larger monolithic protocols cannot safely support. Silo's architecture allows the Hyperliquid ecosystem to support lending for any HIP-1 token without threatening the security of other markets.

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Feature Comparison

FeaturePyth Network logoPyth NetworkSilo Finance logoSilo Finance
LayerMulti-LayerMulti-Layer
CategoryOraclesLending & Borrowing
StatusActiveActive
Launch Year
Websitepyth.networksilo.finance
Twitter
GitHubNot publicNot public
VerifiedUnverifiedUnverified
Tags

Score Comparison

Pyth NetworkSilo Finance
Open Source
Pyth Network
Not public
Silo Finance
Not public
Verified
Pyth Network
Unverified
Silo Finance
Unverified
Ecosystem Breadth
Pyth Network
0 tags
Silo Finance
0 tags
Maturity
Pyth Network
Unknown
Silo Finance
Unknown

Feature Matrix

FeaturePyth Network logoPyth NetworkSilo Finance logoSilo Finance
Open Source
Verified
Has Website
Has Twitter
Has GitHub
Active Status

Key Differences

Category Focus

Pyth Network is focused on oracles, while Silo Finance targets lending & borrowing. They serve different user needs within the Hyperliquid ecosystem.

When to Use Each

Choose Pyth Network if you...

  • Want a oracles solution on Multi-Layer
  • Need: High-fidelity oracle delivering real-world market data to Hyperliquid

Choose Silo Finance if you...

  • Want a lending & borrowing solution on Multi-Layer
  • Need: Isolated lending markets ensuring risk containment for any token on HyperEVM

Ecosystem Integration

Pyth Network logo

Pyth Network

Pyth Network operates on Multi-Layer (spans multiple hyperliquid layers). Spanning multiple layers lets it combine the strengths of each, though integration complexity is higher.

Silo Finance logo

Silo Finance

Silo Finance operates on Multi-Layer (spans multiple hyperliquid layers). Spanning multiple layers lets it combine the strengths of each, though integration complexity is higher.

Both protocols share the same layer, maximizing composability potential.

Community Verdict

Which do you prefer?

Share your experience with Pyth Network or Silo Finance to help others in the Hyperliquid community make better decisions.

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