Bittensor Ecosystem
A complete overview of the Bittensor network - 128 subnets across 17 categories, plus infrastructure, wallets, exchanges and developer tools.
Subnets by Category128 total
Other
18 subnetsDeFi
15 subnetsData
12 subnetsPredictions
11 subnetsMedia
11 subnetsSecurity
10 subnetsAgents
9 subnetsTraining
8 subnetsScience
8 subnetsCompute
7 subnetsMining
3 subnetsRobotics
3 subnetsDeveloper Tools
2 subnetsSports
1 subnetsStorage
1 subnetsHow We Categorize Subnets
Each subnet is categorized based on its primary function: what it actually does for the network. Categories are assigned manually based on the subnet's documentation, GitHub repository, and on-chain activity. Some subnets span multiple areas (e.g. a training subnet that also serves inference), but we pick the dominant function.
Serving AI models to users
Training & fine-tuning models
Collecting & curating datasets
Raw GPU, infrastructure, mining
Liquidity, lending, trading
Forecasting & oracle networks
Auditing, detection, privacy
Autonomous AI agents
Research & scientific compute
Video, audio, content creation
Games & virtual worlds
Drones, autonomous vehicles
Decentralized file storage
Sports analytics & signals
SDKs, testing, tooling
How Health Scores Work
Every subnet gets a health score from 0-100 based on four pillars. Scores use percentile ranking, so a subnet in the top 5% for a metric scores ~95 on that component. This means the score reflects how a subnet compares to all others, not arbitrary thresholds.
Liquidity & Market (30%)
TAO locked in the pool, market cap, and trading volume. Higher liquidity means less slippage and more confidence from stakers.
Network (30%)
Validator count, miner slot utilization, and miner-to-validator ratio. A well-populated subnet signals real demand for its services.
Emission & Incentive (20%)
TAO emission received, registration cost demand, market confidence, subnet age (older = more proven), and tempo efficiency.
Growth & Momentum (20%)
Buy/sell ratio (money flowing in or out), 7-day price trend, trend consistency, and trading volume. Stable or growing subnets score well.