Hasan Toor introduces Ling-flash-2.0 with 6.1B active parameters

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Ivan Andriyenko

19.09.2025

Hasan Toor introduces Ling-flash-2.0 with 6.1B active parameters — @hasantoxr: Ling-flash-2.0 AI breakthrough

Hasan Toor, through a recent tweet, introduced Ling-flash-2.0, a large language model that significantly outperforms existing counterparts.

This model utilizes 100 billion Mixture of Experts (MoE) parameters with only 6.1 billion active at a time. Toor claims it is three times faster than a 36 billion dense model, processing over 200 tokens per second on H20 infrastructure. Additionally, Ling-flash-2.0 excels in complex reasoning, outperforming models near the 40 billion parameter range. Designed specifically for coding and frontend development, this breakthrough signifies a bold step in AI deployment efficiency, combining smaller active parameter usage with enhanced performance.

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Ling-flash-2.0’s innovative approach to specialized AI solutions builds upon Hasan Toor’s ongoing exploration of emerging technology frontiers, following his introduction of Bika AI as a tool for efficient solopreneur teams. The focus on coding and frontend development in the latest model also resonates with Toor’s earlier advancements in personalized language learning through Midoo AI, highlighting a pattern of targeted, high-performance AI applications across diverse domains.

This material may contain third-party opinions, none of the data and information on this webpage constitutes investment advice according to our Disclaimer. While we adhere to strict Editorial Integrity, this post may contain references to products from our partners.

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