I've been building something new for TensorFold. It's not just another quant. It’s a quantization framework designed around how TensorFold actually runs models. I'm calling it Engine-Aware Quantization, or EAQ. First target: GLM 5.3 Flash. Early results vs my current public quant on the same TensorFold version, measured against the original BF16 model: - 41% lower error on what the model actually writes - 54% lower error on the decisions that matter for agents: when to call a tool, which one, when to stop - roughly the same speed. Built for coding, agentic work and tool calling. This isn't a one-off: the framework is meant to carry over to every model and quant I will build in the future. Still validating on real tool-calling and agent benchmarks before anything goes public. More details coming soon.