➥ You are still fading $RENDER? Ngmi.

@rendernetwork isn’t just another AI narrative token, it’s a live compute marketplace with measurable throughput and a feedback loop most people are still underestimating.
RNP-023 just passed with near-total consensus (3.6M YES vs 17.6K NO), onboarding ~60K daily GPUs via Salad as a dedicated subnet.
That’s not incremental growth, that’s a supply-side step change. More capacity → more jobs → more on-chain settlement in $RENDER → higher burn velocity via BME.
》Network data already confirms the shift:
• 71M+ frames processed
• ~35–40% of workloads now AI/ML
• 5,700+ active nodes
• 1.24M+ $RENDER burned
This is no longer a “rendering network”, it’s evolving into a generalized compute layer where AI demand is becoming the dominant load driver.
The key design most overlook is the Burn-and-Mint Equilibrium. Demand (compute jobs) burns $RENDER, while supply (GPU providers) is minted against real usage.
> Net effect: token dynamics are directly coupled to throughput, not speculation.
》Zooming out:
Global AI compute demand is structurally outpacing centralized supply.
Render aggregates idle GPUs into a permissionless market, effectively acting as a liquidity layer for compute.
Add Salad’s scale, rising AI workload share, and a usage-linked token model, and you get a system where growth reinforces itself:
More GPUs → more jobs → more burns → stronger demand for $RENDER
It’s one of the few networks where the fundamentals aren’t theoretical.
The usage is there, the economics are active, and the system is compounding.