Ash Hart(@ashxhart):A lot of speed-up tricks for AI inference engines sacrifice the quality or accuracy of the answers TensorFold uses exact speculative decoding to get you the main model's answer faster. A drafter proposes several tokens ahead (batched). The main model checks them together, keeps the matching prefix and corrects the first mismatch. With the same TensorFold setup, prompt and seed on a supported decoding path, the output matches drafting off, token for token. The main model still decides the answer, you just spend less time waiting for it. https://t.co/H2dBxCSaUV @tensorfold

2026.10.31 10:38

A lot of speed-up tricks for AI inference engines sacrifice the quality or accuracy of the answers TensorFold uses exact speculative decoding to get you the main model's answer faster. A drafter proposes several tokens ahead (batched). The main model checks them together, keeps the matching prefix and corrects the first mismatch. With the same TensorFold setup, prompt and seed on a supported decoding path, the output matches drafting off, token for token. The main model still decides the answer, you just spend less time waiting for it. @tensorfold_dev