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M
Dex

Meteora DLMM

Best for documented on-chain trading

Total value locked:$173m at this checkChains:1Audits recorded:0Audit report linked:Not foundRubric:v2.0 · verified 9 Aug 2026
Kayla PetersonKayla PetersonDeFi Research Analyst· Last verified August 9, 2026
Confidence ARubric v2.0Verified August 9, 2026
7.1
out of 10
Open account
Scorecard

How it rates

Counterparty & contract risk · 30%6.0
Cost transparency · 20%9.0
Market quality · 25%6.0
Transparency & track record · 15%8.0
Public documentation surface · 10%8.0
Pros
  • Documentation published at a public address
Cons
  • No audit report linked in the public dataset at this check
  • Single-chain deployment
How this score was built

Each indicator scores 2, 1 or 0. A pillar is the points earned over the points available; the overall score is the weighted sum. Every source below is public — check any of them yourself.

Counterparty & contract risk · 30% weight6/10 points · 6.0/10
Cost transparency · 20% weight9/10 points · 9.0/10
  • Met
    Documentation published where fees are described

    Documentation reachable for fee review.

    docs.meteora.ag/
  • Met
    Application reachable without an account

    No account required to reach the app.

    app.meteora.ag/
  • Met
    Independent dataset publishes protocol economics

    TVL and change history published independently.

    defillama.com/protocol/meteora-dlmm
  • Partial
    Fee model documented publicly

    Documentation available; specific fee tiers not captured at this check.

    docs.meteora.ag/
  • Met
    No account required to read protocol documentation

    Open documentation.

    docs.meteora.ag/
Market quality · 25% weight6/10 points · 6.0/10
Transparency & track record · 15% weight8/10 points · 8.0/10
Public documentation surface · 10% weight8/10 points · 8.0/10

A Solana liquidity protocol using discrete price bins rather than a continuous curve, holding $173m with configurable liquidity distribution shapes.

Our assessment

Meteora's Dynamic Liquidity Market Maker replaces the continuous curve with discrete price bins. Inside a bin, trades execute at a single price with no slippage at all; the price moves only when a bin is exhausted. It holds $173m on Solana at this check.

Bins are a different trade-off from curves

A curve prices every trade slightly differently. Bins behave like a stack of limit orders, which produces exact execution within a bin and lets providers shape their distribution — flat, curved, or weighted to one side. For a provider with a view on where price will sit, that expressiveness is real.

Expressiveness raises the skill floor

Choosing a distribution shape is a decision most liquidity providers are not equipped to make, and choosing badly concentrates capital exactly where it will be adversely selected. This is a tool for providers who understand what they are doing; passive capital does better in a simple stable pool.

No audit report at a public address

No linked audit report was retrievable at this check. Novel liquidity mathematics carries more model risk than a well-worn constant-product pool, and a published review would be worth more here than for a protocol running code that has been attacked unsuccessfully for years.

Who it suits

Meteora fits sophisticated Solana liquidity providers who want control over their distribution and understand adverse selection. Passive providers and ordinary traders will get more from Orca or Raydium.

Alternatives

How rivals compare

ServiceScoreBest for
Uniswap V39.8audited, multi-chain deploymentRead →
Curve DEX9.6audited, multi-chain deploymentRead →
PancakeSwap AMM9.6audited, multi-chain deploymentRead →
Reference

Frequently asked

Does this score mean Meteora DLMM is safe to use?

No. It measures what an outsider can verify: linked audits, published documentation and independently recorded market data. Contract behaviour is not tested by us.

Where does the TVL figure come from?

An independent public analytics platform, queried at the verification date. Anyone can re-run the same query.

Why do some protocols score zero on audits?

Because no audit report is linked in the public dataset. It records what a user can reach, not a claim that no audit was ever performed.