A GitHub-published benchmark claims CoinStats’ crypto AI agent outperformed rival deep research models from Google, OpenAI and Anthropic, signalling a potential edge for domain-specific AI.
An open source crypto deep research benchmark published on GitHub claims CoinStats AI Agent outperformed proprietary deep research tools from Google, OpenAI and Anthropic in both quality and speed, adding momentum to the case for domain-specific AI agents.
In the benchmark, CoinStats AI Agent scored 79 out of 100, ahead of Gemini Deep Research at 67, ChatGPT Deep Research at 61, and Claude Deep Research at 58. CoinStats also reported an average response time of four minutes, versus 23 minutes for Gemini, 22 for Claude, and 55 for ChatGPT.
A notable differentiator is the benchmark’s open-source methodology, which allows researchers to review, replicate or challenge the results. Evaluation covered accuracy, depth, recency and actionability.
CoinStats attributes the performance gap to direct access to onchain data, exchange metrics, derivatives information and real-time social sentiment, combined through a multi-agent “agentic orchestration” architecture that runs specialised agents in parallel.
The beta-stage platform also supports market research, onchain tracking across more than 120 blockchains, sentiment analysis, backtesting, code execution and interactive visual outputs. It offers Deep Research, Backtesting and Fast modes, alongside a Private Mode powered by Venice AI.
CoinStats said the results support the view that vertical AI systems can outperform general-purpose models in specialist research workflows.
