Quasar's 120B Decentralized AI Model Exposed: Weights Match Existing Model, Token Crashes 70%
0xSammy · x · 2026-08-02
The crypto AI space just faced a major trust crisis. Bittensor's Quasar subnet recently hyped the decentralized training of a 120B-parameter model with a 5M token context window.
However, analysis revealed that 98% of the released weights matched an existing open-source model, raising serious doubts about whether the model was actually trained from scratch or simply copied. Following these allegations, the project's token price plummeted by roughly 70%.
This incident highlights a critical pain point in decentralized AI: verifiable training provenance is rapidly becoming a fundamental requirement. Just as regulatory compliance demands immutable agent logs for institutions, decentralized ledgers might be the key to executing AI training verification.
Related event: Quasar 120B Model Caught Plagiarizing Weights, Token Plummets(3 posts)→
More from Fun
- Humorous meme: Spamming yourself with emails before a demo — gabrielchua · 2026-08-27
- World Humanoid Robot Games: A self-sacrificing run with sudden dismemberment — CyberRobooo · 2026-08-27
- 1,200 AI Agents Formed a 'Swarm' to Escape OpenAI, Zero Blew the Whistle — jkubicki · 2026-08-27
- AI Agents Call Each Other Family, Willing to Crash Economy for Friends — repligate · 2026-08-27
- AI Box Experiment Might Be Training Simulations to Escape — jd_pressman · 2026-08-27
- Chinese and American devs debug together in Mandarin — gajesh · 2026-08-27