Zero Gravity

Check 0G to INR price here

• 0G is a modular blockchain built for artificial intelligence workloads, combining data availability, storage and a compute network.

• Its data availability layer is designed for the throughput AI datasets require rather than ordinary transaction data.

• 0G is the gas, staking and governance tokens of the network Check 0G to INR price here.

• Supply at the token generation event was 1 billion, allocated 28% to ecosystem growth, 22% to the team, contributors and advisors, 22% to backers, 15% to AI Alignment Nodes and 13% to community rewards.

• Some data trackers list total supply as uncapped because of ongoing network rewards, so check the protocol's current documentation for the emission schedule.

• Staking secures the network and pays storage and compute providers.

Pros:

• Purpose-built for AI data throughput rather than adapting a general chain.

• Raised substantial capital with backing from established crypto and technology investors.

• Mainnet is live rather than prospective.

Cons:

• Supply mechanics are documented inconsistently across sources, which is itself a governance concern.

• Performance claims are large and difficult to verify independently under real load.

• On-chain AI remains a thesis rather than a demonstrated market.

• Exposure to AI-specific blockchain infrastructure with a live network.

• Funding and partnerships give it runway most competitors lack.

• Resolve the supply question before treating the token's economics as understood.

• A data availability layer sized for AI datasets rather than transaction batches, which no general-purpose chain currently offers.

• AI workloads generate data volumes that ordinary blockchain data layers cannot carry at any reasonable cost.

• Separating storage, availability and compute into dedicated layers makes the throughput economically possible.

• Founded by Michael Heinrich, Thomas Yao, Ming Wu and Fan Long, operating as 0G Labs.

• Backed by Hack VC, Delphi Digital, Animoca Brands and others.

• No conventional public ICO. Funding came through equity rounds and token purchase commitments, with public distribution via airdrop and exchange programmes.

• Inconsistent public documentation of supply is a material disclosure problem.

• Demand for on-chain AI infrastructure is unproven at scale.

• Large investor allocations with multi-year unlocks.

• Competing AI-focused chains target the same thesis.