webAI releases TwIL-8B reasoning model
MarkTechPost: webAI Releases TwIL-8B, an 8.8B Reasoning Model Scoring 98.2 on MATH-500
webAI has released TwIL-8B, an 8.8B reasoning model for math, code and instruction following. The TwIL-8B reasoning model is post-trained from IBM’s Granite 4.2 8B. Weights are on Hugging Face under a non-commercial license. webAI’s launch post frames the pitch around cost per task, not raw scale. The 4-bit build is 4.98 GiB, sized for CPU or modest-VRAM GPU inference. TL;DR Size: 8.79B parameters, dense. 131,072-token context, inherited from the base model. Runs on: CPU o
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webAI has released TwIL-8B, an 8.8 billion parameter reasoning model designed for math, code, and instruction following tasks that was built by post-training IBM's Granite 4.2 8B model. The model achieves a score of 98.2 on the MATH-500 benchmark, the highest score in webAI's comparison, and uses 38 percent fewer reasoning tokens than a comparable competitor model while achieving slightly lower scores on some benchmarks. TwIL-8B is optimized for efficiency and can run on standard computers with modest graphics processing power, with weights available under a non-commercial license, though it performs notably weaker on knowledge-based benchmarks compared to other models of similar size.
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