Bittensor coordinates open AI markets. Subnets set the tasks, miners provide the work, validators score quality, and TAO pays for performance. TorchRank makes the live data legible so you can delegate, validate, or provide compute with confidence.
Think of subnets as specialized arenas for AI work (search, agents, embeddings, diffusion, etc.). Miners/models do the work, validators score it. Consistent quality earns more TAO.
Independent zones for specific AI tasks. Each sets its rules, inputs, and reputation loop.
Score outputs and direct rewards. Better curation → better network performance and incentives.
Bring models + compute. Accuracy, uptime, and latency win. TAO rewards follow real value.
Pick the lane that fits your ops appetite and desired upside.
Back proven validators and share rewards with minimal maintenance. Use TorchRank to find consistency.
Operate scoring logic and curate quality. More work, more control, potential for higher real yield.
Supply the horsepower for subnets. Optimize hardware + uptime where the economics are favorable.
Demand for AI is exploding but centralized. Bittensor shifts it into open markets with transparent performance and pay-for-results.
Competition and price discovery for intelligence, not just for compute time.
Rewards follow consistent performance and uptime. Incentives push reliability over hype.
Subnets can call each other — agents, vision, embeddings — like Lego for AI.
Think “points that become payouts,” allocated to the most useful, reliable work.
// Back-of-napkin validation math
reward_share = subnet_emissions * your_score_share
net_yield = (reward_share * (1 - fee)) - (infra_cost + ops_cost)
// Scale only if your 7–14 day consistency stays strong.We turn raw network data into clear, human-readable rollups so you can act fast and defend decisions later.
Minute, hour, and day snapshots surface who performs every day — not just on launch day.
Cards and tables tuned for quick reads: who’s real, who’s slipping, where the trend’s going.
Drilldowns, history, and exports for informed delegation, validation, and compute placement.
A specialized zone for one kind of AI work. Each has its own rules and reputation incentives.
Validators curate and earn fees for quality scoring. Delegates back them to share rewards with low effort.
Stable performance over time — the best predictor of durable rewards.
Scan featured subnets on the homepage, then open validator drilldowns and check 7–30 day history.