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Ruliad AI has introduced DeepThought-8B, a new reasoning model built on the LLaMA-3.1 architecture. This model features test-time compute scaling and is designed to enhance transparency in AI reasoning. DeepThought-8B operates on approximately 16GB of VRAM, making it competitive with larger models, specifically those with 70 billion parameters. The model supports JSON-structured thought chains and controllable inference paths, which aim to make AI reasoning more accessible and comprehensible. Open model weights and inference scripts are also provided, allowing for broader use and experimentation within the AI community.
Ruliad AI Releases DeepThought-8B: A New Small Language Model Built on LLaMA-3.1 with Test-Time Compute Scaling and Deliverers Transparent Reasoning https://t.co/ULiZI3L0b9 #Deepthought8B #RuliadAI #AIModels #TransparentReasoning #MachineLearning #ai #news #llm #ml #research … https://t.co/lg8ARBaLH3
Ruliad AI Releases DeepThought-8B: A New Small Language Model Built on LLaMA-3.1 with Test-Time Compute Scaling and Deliverers Transparent Reasoning Deepthought-8B distinguishes itself with unique features aimed at making AI reasoning more accessible and understandable. The… https://t.co/bT9leXltQB
Another open-source reasoning model just dropped 🔥 Runs on 16GB consumer GPUs. → DeepThought-8B built on LLaMA-3.1 focuses on transparent reasoning through structured JSON outputs → Performance rivals 70B model's while requiring only 16GB VRAM, making it accessible for… https://t.co/m2LXRXb8b9
