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An index tracking realtime GPU rental prices and a perpetual futures marketplace that trades it

1 starsRust

GPU Perpetual Futures Prototype

by ozzymandiaz96·Feb 15, 2026·9 points·3 comments

AI Analysis

●●●BangerBig BrainBold BetWizardry

GPU derivatives with real funding rates and mark pricing—fills a genuine infrastructure hedging gap.

Strengths
  • Novel application domain: GPU compute hedging mirrors mature commodity derivatives (fuel, coffee), legitimizes the category.
  • Event-driven Rust backend with supervisor pattern and circuit breakers shows serious engineering discipline beyond MVP.
  • Real index + funding mechanics ground the prototype in actual finance—not a toy simulator, though order matching is simulated.
Weaknesses
  • Single-client demo with simulated order book limits credibility as a tradeable platform; multi-client matching is table stakes.
  • Unclear if market demand exists: no validation that GPU operators/traders actually want this hedging tool in practice.
Category
Target Audience

ML labs, cloud operators, quantitative traders, GPU rental marketplaces seeking compute cost hedging.

Similar To

Hyperliquid (perpetual futures interface) · dYdX (derivatives platform template) · Vast.ai (GPU rental marketplace)

Post Description

GPU rental prices are super volatile but there's no derivatives market to hedge. I built a perpetual futures platform to see what this could look like.

The idea is airlines hedge jet fuel, starbucks hedges coffee beans - as GPU compute becomes critical infrastructure the same hedging tools should exist. Not sure if anyone actually needs this but it was interesting to build.

How it works: - Pulls live H200 spot prices from Vast.ai every 15s into a tradeable index - Full perp mechanics: funding rates, mark price calc, real-time P&L - Event-driven Rust backend with supervisor pattern and circuit breakers - Next.js frontend with TradingView charts, real-time WebSocket updates

What's real vs simulated: - Real: Index construction, funding rate engine, forward curve, state persistence - Simulated: Order book depth and trade matching (its a single-client demo)

The backend is the part I'm most proud of - isolated tasks coordinated by a supervisor, each has it's own state machine so if one component fails it doesn't take down the others. Tried to build it with production patterns in mind even though its just a demo.

Also made a 15-page derivatives pricing doc that covers the economic model and hedging scenarios. Basically: rental prices = f(CAPEX, utilization, depreciation) so futures pricing reveals market expectations about GPU supply/demand.

GitHub: https://github.com/zacharyfrederick/compex

Would love feedback on the architecture or if the market mechanics actually make sense. First time building something like this.

Similar Projects

Infrastructure●●Solid

I track GPU rental prices – same H100 ranges from $0.80 to $3.19/HR

It normalizes messy provider offers into a single table with filters for VRAM, NVLink, on‑demand vs spot, and 'in‑stock only' — exactly the controls you want when hunting GPUs. The UI is clear and fast (filters, region/provider lists, a cost calculator beta), but underneath it's still an aggregator with affiliate ties and scraping cadence risks, so expect to verify prices on the provider before launching.

Solve My ProblemSlick
hwspeed
213mo ago