webAI 开源 88 亿参数小模型 TwIL-8B，编码与数学成绩接近前沿模型

Another great open-source model release. TwIL-8B shows strong results on coding, instruction-following, and math benchmarks. I'm bullish on small models we can run locally and on our own hardware. As we unlock efficient intelligence and capabilities, smaller models will play a significant role in more complex agentic workflows like scientific discovery and software factories. David Stout @Davidstout Modest intelligence is arriving faster than most people realize. Today, we're open-sourcing TwIL-8B. Just 8.8 billion parameters, yet approaching frontier-model scores on several difficult benchmarks: • 93% of frontier performance on coding • 92% on instruction following • 90% on contest mathematics All from a model small enough to run on your own hardware. But the benchmarks aren't the most important part of this announcement. For years, the AI industry has focused on building the most capable model, regardless of the cost required to run it. I believe that equation is changing. The next era of AI will be defined by the cost of completing work. Not simply the intelligence of the model, but how efficiently that intelligence can accomplish the task. If a model with 8 billion parameters can reliably complete the same work as one with hundreds of billions, why pay for the larger model? As smaller models become more capable, intelligence becomes something we can distribute, specialize, and run across the hardware we already own. That's the future we're building at @thewebAI TwIL-8B is available today. Open weights. And this is just the first of several announcements we're making today. HF Link: huggingface.co/webAI-Official… Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 10 🔄 1 ❤️ 14 👀 1977 📊 8 ⚡