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借贷质押借款Stablecoins
  1. Bitcompare
  2. 币种
  3. Sushi (SUSHI)
  4. 借贷利率

Sushi 借贷指南

如何借出Sushi
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Sushi (SUSHI) 借贷利率

找到最高的SUSHI借贷利率,赚取高达12% APY APY。并排比较1个平台。

Updated: 2026年5月31日
12% APY
最高利率

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The best Sushi lending rate is 12% APY on YouHodler.. Compare SUSHI lending rates across 1 platforms.

YouHodler12%

比较Sushi (SUSHI) 借贷利率

平台操作最高利率基础利率最低存款额锁定期CN地区可用性
YouHodler前往平台12% APY———查看条款

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显示第 1 至 1 条,共 1 条结果

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Sushi历史借贷利率(中国)

显示的利率是我们为中国用户跟踪的主要利率;实际利率可能因产品、级别或条款而异。

Loading chart...
过去30天内OKX, YouHodler, Gemini利率对比图表

OKX目前在中国提供最高的Sushi借贷利率,为44.16%APY,高于30天平均值39.69%。

30天平均利率箭头比较今天与30天平均值

供应商当前利率趋势平均利率
OKX
44.17%均 39.69%
YouHodler
12%-均 12%
Gemini
0.01%-均 0.01%
最佳30天平均OKX (39.69% APY)
最后更新:2026年5月31日 04:11

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关于借贷 Sushi (SUSHI) 的常见问题

What geographic restrictions, minimum deposit requirements, KYC levels, and platform-specific eligibility constraints apply to lending Sushi across its supported platforms?
The provided dataset does not specify any geographic restrictions, minimum deposit requirements, KYC levels, or platform-specific eligibility constraints for lending Sushi. While it confirms that Sushi lending spans multiple networks (described as multi-chain lending coverage across 14 networks) and lists 14 supported platforms (base, celo, sora, energi, fantom, katana, solana, ethereum, avalanche, polygonPos, arbitrumOne, nearProtocol, harmonyShard0, binanceSmartChain), there are no explicit policy details in the data about where lending is allowed, the minimum amount to deposit, the identification requirements, or any platform-by-platform eligibility rules. What is available numerically includes: - Platform count: 14 networks/platforms - Current price: 0.193153 USD - 24-hour price change: +2.96% - Market cap: 52,740,523 USD Because policy specifics are not present, you should consult each platform’s own lending terms for Sushi to determine geographic allowances, KYC tiers, minimum deposits, and any platform-specific eligibility constraints. The platforms listed (e.g., Ethereum, Solana, Binance Smart Chain, Arbitrum, Polygon, etc.) may each implement their own KYC and deposit rules, so per-platform documentation is required for precise, actionable guidance.
What are the typical lockup periods, potential insolvency risk of the lending platform, smart contract risks, rate volatility, and how should an investor evaluate risk versus reward when lending Sushi?
Based on the provided context, there is no explicit data on lockup periods or lending rates for Sushi (rates array is empty). The material does indicate multi-chain lending coverage across 14 networks, which suggests a broad, cross-chain exposure rather than a single-chain risk. Sushi’s current price is 0.193153 with a 24-hour price change of +2.96%, and its market cap is ~$52.74 million with a circulating supply of about 273.01 million SUSHI out of ~291.51 million total. This implies a relatively modest capitalization for a cross-chain asset, which can influence liquidity and funding risk in lending markets. The platform count (14 networks) signals diversification across multiple ecosystems, potentially reducing protocol-specific insolvency risk compared with a single-chain project. However, the context provides no concrete insolvency metrics, reserve data, or health indicators for any given lending market, so insolvency risk cannot be quantified here. Likewise, there is no rate data or volatility history for Sushi’s lending rate, so rate volatility and upside/downside potential cannot be measured from the given information. Smart contract risk is not described in the context; general risks (code bugs, upgrades, and governance changes) would apply, but no specifics are given. For evaluating risk vs reward, investors should seek: (1) explicit lockup terms from the lending platform, (2) current and historical lending APR/APY data, (3) platform solvency disclosures or third-party audits, and (4) detailed smart contract audit reports and exposure across each connected network.
How is Sushi lending yield generated (e.g., DeFi protocols, rehypothecation, institutional lending), are rates fixed or variable, and what is the typical compounding frequency?
Sushi’s lending yield framework, as reflected by the available data, relies on DeFi-style, multi-chain lending activity across a broad network set rather than a single centralized book. The context notes “multi-chain lending coverage across 14 networks,” which implies that lending yield would be generated by liquidity provision and borrowing activity deployed via Sushi-enabled protocols on multiple chains (the listed platforms include Ethereum, Solana, Polygon, Arbitrum, BSC, Avalanche, Fantom, and others). The data does not reveal concrete rate specifics for Sushi lending (rates field is empty) nor any fixed vs. variable rate structure or compounding cadence. Consequently, we cannot confirm whether yields are fixed or variable for Sushi within this dataset, nor can we confirm the exact compounding frequency (as these depend on the individual DeFi protocol implementations and on-chain compounding rules). What is measurable from the data are the broader signals: 14 networks of coverage and active lending-oriented activity, a current price of 0.193153, a 24-hour price uptick of 2.96%, a market cap around $52.74 million, and substantial liquidity indicators such as totalSupply (~291.5 million) and circulatingSupply (~273.0 million). In practice, Sushi lending yields would be shaped by the aggregate DeFi liquidity, utilization, and borrowing demand across these networks, with protocol-specific terms (potentially variable rates) and protocol-defined compounding frequencies. Until rate tables or protocol docs are provided, precise fixed/variable classification and compounding schedules cannot be stated from this dataset.
Based on the data, what is Sushi’s most distinctive feature in its lending market (such as notable rate changes, unusually broad platform coverage, or a unique market insight)?
Sushi’s most distinctive feature in its lending market is its breadth of cross‑chain coverage. With lending support across 14 networks, Sushi asserts a uniquely multi‑chain footprint relative to typical single‑chain lenders. The platform list includes Ethereum, Solana, Binance Smart Chain, Polygon (PolygonPos), Arbitrum One, Avalanche, Fantom, Near Protocol, Harmony Shard0, Celo, Sora, Energi, Katana, and Base, signaling a broad, cross‑ecosystem liquidity reach. This extensive network coverage (platformCount: 14) enables borrowers and lenders to access funds across diverse ecosystems within a single lending framework, which can reduce cross‑chain friction and widen available liquidity pools. The ecosystem is also experiencing healthy near‑term activity signals, evidenced by Sushi’s 24h price rise of 2.96%, indicating rising market attention and potential demand in its lending markets. Overall, the standout feature is the platform‑wide, multi‑chain lending capability, as opposed to isolated, chain‑specific lending offerings.

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