Top 5 AI coins showdown: Who is the true king of Computing Power?

Current Status Overview

As of August 2024, the top five AI+ blockchain projects by market capitalization are: NEAR( $4.68 billion), ICP( $3.64 billion), ASI( $2.8 billion), Render( $2.04 billion), and Bittensor( $2.03 billion). These five projects each follow completely different paths, but they are all trying to integrate AI capabilities into blockchain.

Breakdown of Each Company's Roadmap

NEAR follows an infrastructure route - the Nightshade sharding technology allows it to process thousands of transactions per second, and it is now using AI to optimize validator scheduling and help developers automatically generate smart contract code. In simple terms: it speeds up DApps while lowering the development threshold.

ICP plays with great ambition—executing AI models directly on the chain without relying on centralized cloud services. This is particularly useful for DeFi, allowing AI to optimize trading strategies and risk warnings in real-time, and even to automatically execute financial logic.

ASI is an alliance: Fetch.ai + SingularityNET + Ocean Protocol have merged, aiming to build an ecosystem of “autonomous agents + open-source AGI + data trading.” The core selling point is that AI agents can negotiate, execute contracts, and optimize resource allocation on their own—making them the “robotic employees” on the blockchain.

Render is simply about turning idle graphics cards into rendering clouds. The role of AI here is to intelligently allocate GPU tasks, optimize rendering parameters, and enhance image quality. This significantly lowers the barrier for creators.

Bittensor is the most radical - it builds the entire protocol on AI, where miners contribute computing power and data to train models. The protocol uses AI to assess the quality of contributions and distribute TAO rewards. It is equivalent to creating a decentralized AI factory.

The core difference is here

These five projects are essentially answering different questions: NEAR and ICP ask “How to make the chain faster and stronger”; ASI asks “How to make AI autonomous”; Render asks “How to democratize computing power”; Bittensor asks “How to decentralize training”.

Who will win? It depends on which direction the market ultimately values AI—whether it's infrastructure efficiency, practical applications, or the concept of decentralization.