Custom GMX Fork Development for Perpetual DEX
We develop GMX forks for perpetual DEXs, adapting the architecture to specific requirements. GMX is not just a protocol—it's a proven architecture: the GLP pool as the counterparty, zero-price-impact order execution (up to a certain threshold), and oracle-based pricing instead of an order book. Forking GMX is not "copying contracts"; it's understanding the risk management system between LPs and traders and adapting it to your goals.
Our blockchain development experience exceeds 10 years, and we have successfully deployed 5+ GMX forks on L2 networks, maintaining 99.9% uptime of the keeper network. Order a GMX fork development from us—we will audit your requirements and propose the optimal architectural solution.
How Does GLP Manage Risk?
In GMX v1, liquidity providers deposit assets into the GLP vault—a multi-asset pool acting as the counterparty for traders. When a trader opens a long on ETH, they borrow ETH from the GLP (via the reserved amount mechanic). If the price rises, GLP loses; the trader wins—and vice versa. GLP profitability correlates with the percentage of losing traders. The balance is maintained by fees and the size of open positions.
When forking, you must explicitly decide: which assets enter the pool? What is the maximum allocation per asset (in GMX: ETH ~35%, BTC ~25%, stablecoins ~40%)? How is rebalancing managed via dynamic mint/redeem fees? Incorrect allocation balance leads to pool insolvency risk under directional market pressure.
Why Is Protection Against Oracle Manipulation Important?
GMX uses Chainlink + Binance/Coinbase price aggregation with a bid/ask spread. The spread between them is the primary defense mechanism. A position is opened at ask and closed at bid. In GMX v2, a synthetic market through GLV vault and a keeper system eliminating MEV was introduced.
If you use only Chainlink without a custom price aggregator, a latency of 1–3 blocks during extreme volatility creates a window for price arbitrage. Several GMX v1 forks have lost funds due to this—traders opened positions knowing the next oracle price. We implement multi-oracle aggregation with dynamic spread and deviation monitoring.
What Risks Does a GMX Fork Carry?
Main risks: oracle arbitrage during volatility, bad debt from non-liquidated positions, keeper network failure, suboptimal GLP pool balance. For example, during a black swan event without ADL (Auto-Deleveraging), the pool may become insolvent. We minimize risks through redundant keepers, fuzz testing, and strict risk-management parameters.
How to Prevent Bad Debt and Liquidations?
In GMX, a position is liquidated when losses + fees exceed collateral minus liquidationFeeUsd. The problem: during extreme movements, a position can become negative collateral faster than a keeper can liquidate—resulting in bad debt. In v2, this is solved via ADL: when utilization is high, the most profitable positions are forcibly closed. A fork without ADL risks systemic insolvency during a black swan.
Fork Architecture and Key Changes
| Contract | Role | What We Change in the Fork |
|---|---|---|
| Vault | Asset storage, P&L calculation | Fees, supported tokens |
| GlpManager | Mint/redeem GLP | Basket composition, limits |
| PositionRouter | Order management | Execution fee, delay |
| OrderBook | Limit/stop orders | Tick size, min size |
| PriceFeed | Oracle aggregation | Sources, spread logic |
| RewardRouter | Staking, APR distribution | Emission schedule |
In GMX v1, the codebase is written in Solidity 0.6.x. We migrate to 0.8.x with explicit overflow protection, removing SafeMath and enabling built-in compiler checks.
What Is Keeper Infrastructure?
For a production fork, keeper infrastructure is required: at least 2–3 keepers with failover, monitoring of pending orders, automatic gas increase for stuck transactions. The keeper is critical infrastructure—if it fails, orders are not executed, liquidations do not occur, and the pool accumulates risk. We build keeper systems in TypeScript with viem, a Redis queue for pending orders, Prometheus metrics, and PagerDuty alerts. Execution latency must be <2 blocks from the moment an executable position appears.
Technical details of keeper architecture
The keeper monitors IncreasePositionRequest and DecreasePositionRequest events. When a new event appears, it forms a multicall with executeIncreasePosition or executeDecreasePosition. To avoid race conditions, it uses a Redis lock for each position. In case of an error (e.g., out-of-gas), it retries with increased gas price.
Comparison of GMX Versions
| Parameter | GMX v1 | GMX v2 |
|---|---|---|
| Liquidation | Keeper call | Keeper + ADL |
| Oracle | Chainlink + aggregation | Synthetic markets |
| Fee | 0.1% trading fee | Dynamic |
| Pool composition | Fixed weights | Flexible basket |
What's Included in the Work
- Audit and documentation of smart contracts
- Setup of keeper infrastructure with monitoring
- Integration of The Graph subgraph for position history
- Frontend adaptation (TradingView, wagmi, viem)
- Team training and post-launch support
Process of Work
Analysis (1 week). Audit of target chain (Arbitrum, Avalanche, Base—GMX forks live on L2 due to gas costs), competitive analysis, tokenomics.
Design (1–2 weeks). Adaptation of contracts, storage layout, asset list, risk-management parameters (max leverage, max OI per market).
Development (6–10 weeks). Smart contracts + keeper infrastructure + subgraph + frontend.
Testing (2 weeks). Fork tests with cascade liquidation simulations, oracle latency, keeper failure. Fuzz tests for PnL and liquidation logic.
Audit. Two independent external auditors before mainnet.
Deployment and monitoring. First testnet with real keepers, then mainnet with limited positions for the first 30 days.
Timeline Estimates
A GMX v1 fork on a new EVM chain with a custom pool composition takes 2–3 months. A GMX v2 fork with a full keeper system and subgraph takes 3–4 months. Timelines include audit and phased launch. The cost is calculated individually based on integration complexity and required customization.
According to GMX documentation, the GLP pool uses a multi-asset basket with dynamic allocation.
Contact us for a consultation—we will help assess the scope of work and propose the optimal solution for your project.