According to @gensynai, Eval 8 of 11 of the Gensyn Middleweight General Reasoning Benchmark market on Delphi is now live, expanding the public test coverage for general reasoning models. source: https://twitter.com/gensynai/status/2003561756833243536 Full benchmarking results are available for independent review on the delphi-middleweight-reasoning GitHub repository. source: https://github.com/gensyn-ai/delphi-middleweight-reasoning With 8 of 11 evaluations live, additional releases remain pending, giving market participants a clear milestone to monitor for subsequent data drops. source: https://twitter.com/gensynai/status/2003561756833243536 For crypto traders tracking AI infrastructure and decentralized compute narratives, the repository provides verifiable, time-stamped results suitable for due diligence workflows. source: https://github.com/gensyn-ai/delphi-middleweight-reasoning

According to gensyn (@gensynai), the full benchmarking results for the Gensyn Middleweight General Reasoning Benchmark market are now available at https://github.com/gensyn-ai/delphi-middleweight-reasoning, allowing traders and researchers to directly review the published results referenced in the announcement (source: gensyn (@gensynai) X post on Dec 21, 2025; source: Gensyn GitHub repository at https://github.com/gensyn-ai/delphi-middleweight-reasoning). For trading workflows focused on decentralized AI compute and AI-crypto infrastructure, the repository link provides the official dataset to compare model performance within this benchmark and to track any updates pushed to the repo over time (source: Gensyn GitHub repository at https://github.com/gensyn-ai/delphi-middleweight-reasoning).

According to @gensynai, Gensyn CEO @fenbielding stated that GPU capacity is not limited if there is a system to trust participating hardware, highlighting that scale depends on trust and verification rather than a finite GPU count; source: Gensyn (@gensynai) on X, Dec 18, 2025. For traders, this positions decentralized AI compute as a scale-out model contingent on verifiable trust systems when assessing adoption risk and potential network throughput; source: Gensyn (@gensynai) on X, Dec 18, 2025.

According to @gensynai, Delphi will shift from test tokens to real economic value as mainnet approaches, using game-theoretic incentives to secure execution and verification so all market participants have true skin in the game. source: @gensynai; Gensyn blog For traders, this confirms that economic incentives will directly govern network behavior at mainnet, making the incentive and verification parameters key variables to monitor for participation risk and potential returns once disclosed by the project. source: @gensynai; Gensyn blog

According to @gensynai, the team announced that one million models have been trained on BlockAssist, indicating a large-scale usage milestone for its AI training platform; source: https://twitter.com/gensynai/status/1993319288405364995. The post did not provide details on model sizes, training throughput, costs, or any token/on-chain metrics, so no direct crypto market or token linkage was specified by the source; source: https://twitter.com/gensynai/status/1993319288405364995.

According to @gensynai, the team shipped a new product environment, reported major testnet growth, and released new research in what it called one of its busiest weeks to date (source: @gensynai on X, Nov 17, 2025). According to @gensynai, these updates signal active development and an expanding testnet footprint as described by the project itself, which is relevant for traders tracking decentralized AI compute networks (source: @gensynai on X, Nov 17, 2025). According to @gensynai, the post did not provide specific performance metrics, detailed release notes, or timelines beyond these highlights (source: @gensynai on X, Nov 17, 2025).

According to @gensynai, the Gensyn testnet has reached 1,000,000 models trained, with thanks to node operators, experimenters, and builders; the announcement was posted on Nov 14, 2025. Source: https://twitter.com/gensynai/status/1989127044106735677 The update confirms the achievement pertains to the testnet and provides no details on mainnet timing, token incentives, throughput figures, or other economic metrics. Source: https://twitter.com/gensynai/status/1989127044106735677 For trading context, this is a concrete usage milestone for a decentralized AI compute network but includes no token or on-chain data for valuation or volume analysis. Source: https://twitter.com/gensynai/status/1989127044106735677

According to @gensynai, Gensyn announced that 500,000 models have been trained, providing a concrete usage metric for its decentralized AI compute efforts; Source: https://twitter.com/gensynai/status/1979442229958865060. The post includes a direct link to the project's repository at github.com/gensyn-ai/blockassist, indicating related tooling resources shared alongside the milestone; Source: https://twitter.com/gensynai/status/1979442229958865060 and https://github.com/gensyn-ai/blockassist. The announcement was published on Oct 18, 2025, and does not disclose token, revenue, or detailed technical performance data beyond the 500,000-model figure, limiting measurable takeaways to this single adoption datapoint for traders monitoring decentralized AI and crypto AI sectors; Source: https://twitter.com/gensynai/status/1979442229958865060.

According to @jessepollak, decentralized AI compute services built on the Base blockchain have reached $1 million in annual recurring revenue as of June 2025 (source: Twitter/@jessepollak, June 4, 2025). This milestone signals strong market adoption for AI infrastructure on Base, highlighting growing demand for blockchain-powered AI compute solutions. Traders should watch for increased on-chain activity and token utility related to Base and associated AI projects as this trend may drive upward momentum in related crypto assets.