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Liquid AI reveals 8B-A1B MoE trained on 38T
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Overview
LFM2.5-8B-A1B is an edge model designed for efficient tool calling on consumer hardware, featuring a 128K context window and expanded pretraining from 12 trillion to 38 trillion tokens. The model's vocabulary has been doubled to enhance tokenization for non-Latin languages, enabling it to perform complex tasks on entry-level laptops.
Summary from liquid.ai.
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Hacker News · liquid.ai
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- Praise: Liquid AI's 8B-A1B model demonstrates impressive performance in summarizing long transcripts, showcasing its capabilities despite being a smaller model.
- Praise: The advancements in smaller models, like Qwen3.5:4B, highlight how effective fine-tuning and reinforcement learning can yield high performance on limited hardware.
- Praise: Liquid's focus on model training and fine-tuning allows for the creation of specialized tools that are fast, private, and do not require an internet connection.
- Concern: The 8B-A1B model underperformed significantly in bug fixing benchmarks compared to older models, raising concerns about its competitive edge despite being a newer architecture.
- Concern: There are worries that Liquid AI may be overtraining their models with 38 trillion tokens, which could lead to diminishing returns in performance.