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    CoinStats Launches AI Agent Claiming to Outperform ChatGPT, Gemini and Claude in Crypto Research Benchmark

    The rise of AI agents in crypto reflects a broader trend, as companies increasingly build specialized tools to compete with general-purpose models.
    14 April 2026Updated:14 April 2026
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    Coinstats Launches Ai Agent Claiming To Outperform Chatgpt, Gemini And Claude In Crypto Research Benchmark
    Coinstats Launches Ai Agent Claiming To Outperform Chatgpt, Gemini And Claude In Crypto Research Benchmark

    Crypto tracker app CoinStats has launched a new AI-powered research agent, claiming it outperforms leading models from Google, OpenAI, and Anthropic in crypto-focused deep research tasks.

    The announcement comes alongside the public beta release of the CoinStats AI Agent, a tool designed specifically for cryptocurrency traders and investors.

    Benchmark Results

    According to CoinStats, its AI Agent achieved a score of 79 out of 100 in an internal benchmark evaluating crypto research quality. In comparison, Gemini Deep Research scored 67, ChatGPT 61, and Claude 58.

    Speed was another key differentiator. The CoinStats AI Agent reportedly delivered results in an average of four minutes, while competing tools took significantly longer, with some responses exceeding 50 minutes.

    The company noted that the benchmark methodology is open source and available on GitHub, allowing independent verification of the results.

    Coinstats Launches Ai Agent Claiming To Outperform Chatgpt, Gemini And Claude In Crypto Research Benchmark
    Coinstats Launches Ai Agent Claiming To Outperform Chatgpt, Gemini, and Claude In Crypto Research Benchmark

    Why a Crypto-Native AI?

    CoinStats attributes its performance advantage to its access to specialized data sources.

    Unlike general-purpose AI models, which primarily rely on web data, the CoinStats AI Agent integrates multiple streams of crypto-native information, including on-chain data, exchange metrics, derivatives data, and real-time social sentiment.

    The system uses a multi-agent architecture, where different agents simultaneously analyze various data sources such as news, blockchain activity, and social media trends. These inputs are then combined into a unified research output.

    Key Features

    The CoinStats AI Agent is positioned as a research copilot rather than a simple chatbot, offering several advanced capabilities:

    • Market Research: Explains price movements by combining news, sentiment, and on-chain activity
    • Onchain Tracking: Analyzes wallets, token flows, and blockchain activity across 120+ networks, powered in part by the CoinStats Crypto API
    • Social Sentiment Analysis: Tracks narratives and influencer activity in real time
    • Portfolio Analysis: Provides insights based on a user’s actual holdings
    • Backtesting: Simulates trading strategies using historical data
    • Code Execution: Performs advanced calculations and custom analysis on demand

    The platform also generates visual outputs such as charts and tables, enhancing usability for traders.

    Multiple Modes

    The AI Agent operates across different modes, including:

    • Deep Research: Multi-step analysis across multiple data sources
    • Backtesting: Historical simulation of strategies
    • Fast Mode: Quick answers for simple queries
    • Private Mode: Encrypted processing via decentralized infrastructure, powered by Venice AI

    Availability

    CoinStats AI Agent is currently available in public beta for Degen and Premium users on web, iOS, and Android.

    CoinStats, a crypto portfolio tracking platform founded by Narek Gevorgyan, is positioning this launch as part of its broader move into AI-powered analytics.

    A Growing Trend in Vertical AI

    While the results highlight strong performance in crypto-specific tasks, they are based on internal testing and may vary depending on use cases.

    The launch reflects a broader trend in the AI industry, where specialized, domain-focused tools are emerging to compete with general-purpose models in niche areas such as finance and cryptocurrency research.

    Risk & affiliate notice: Crypto assets are volatile and capital is at risk. This article may contain affiliate links. Read full disclosure

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