AI coins
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Trending AI coins
| Coins | Price | 24h | |
|---|---|---|---|
| | | $ | -5.98% |
| | | $ | -10.35% |
| | | $ | -4.15% |
| | | $ | -5.25% |
| | | $ | -8.29% |
Top gainers
| Coins | | | |||
|---|---|---|---|---|---|
| | | $ | +33.22% | ||
| | | $ | +25.98% | ||
| | | $ | +26.54% | ||
| | | $ | +12.31% | ||
| | | $ | +10.89% | ||
| All gainers | |||||
What is an AI token?
AI tokens are cryptocurrencies that embed artificial-intelligence models, data sets, or services into their core logic.
They power decentralized marketplaces for models, generative-media engines, predictive agents, and on-chain data analytics while using the token for payments, governance, or access rights.
ChatGPT’s late-2022 breakout—and Microsoft’s $10 B OpenAI round—sparked a 75 %-plus rally in early AI tokens, pushing the sector’s market cap past $1.6 B in February 2023.
Quick Facts
- Purpose: Pay for AI inference, training data, agent services; govern AI protocols.
- Utility: Buy GPU compute, query generative models, vote on model upgrades, stake for data quality.
- Chains/Platforms: Ethereum, BSC, Cardano, Fetch.ai native, Ocean Protocol, SingularityNET.
- Pricing: Market-driven; hype cycles tied to AI breakthrough headlines.
- Supply: Usually capped; inflation via mining/mentoring rewards (FET, AGIX).
Top AI Tokens (Live Examples)
| Token | Ticker | AI Focus | 2024 Utility Highlights |
|---|---|---|---|
| SingularityNET | AGIX | Decentralized AI marketplace | Buy/sell models, staking for API calls. |
| Fetch.ai | FET | Autonomous economic agents | Deploy IoT bots, pay for data feeds. |
| Ocean Protocol | OCEAN | Data marketplace | Monetise datasets for model training. |
| Numerai | NMR | AI hedge-fund signals | Stake predictions, earn for accuracy. |
| Alethea AI | ALI | Generative AI & NFTs | Create CharacterGPT NPCs, upgrade NFTs. |
| Cortex | CTXC | On-chain AI inference | Upload AI models to smart contracts. |
How It Works
- Protocol mints token → used as medium of exchange for AI services.
- Developers/Providers stake tokens to list models or datasets.
- Users pay per query (text, image, prediction) in the native token.
- Decentralised GPU or data miners earn tokens for supplying resources.
- Governance votes decide which models or data sources are whitelisted.
Benefits
- Cheaper inference – permissionless competition drives down API costs.
- Censorship resistance – no single entity can de-platform a model.
- Data privacy – federated learning + zk-proofs keep datasets local.
- Tokenised incentives – high-quality data and models are rewarded automatically.
- Composable AI – smart contracts can call AI outputs on-chain (e.g., insurance pricing).
Risks & Limitations
- Compute fraud – malicious nodes may return dummy results; needs reputation or slashing.
- Data quality – poisoned datasets can degrade model accuracy.
- Regulatory grey zone – AI output may be deemed advice or securities signal.
- Token volatility – price swings make enterprise budgeting hard.
- Scalability – on-chain inference is still 10-100× slower than centralised clouds.
- Hype cycles – valuations often detach from actual AI usage metrics.
Final Thoughts
AI tokens sit at the intersection of two exponential trends—large-language-model breakthroughs and open DeFi rails.
They promise democratised access to cutting-edge intelligence, but today most revenue is still speculative.
Trade the narrative, stake for real services, and verify on-chain model usage before aping.