Researchers from Stanford and UC Berkeley Introduce TokenGate: Token-Gated Attention Makes Long-Context Prefill Up to 11.3x Faster

- Stanford and UC Berkeley just dropped TokenGate, a module that prunes LLM tokens to slash prefill time by up to 11.3x. It’s not a new coin, but it is a massive efficiency hack for the AI infrastructure stack. By skipping irrelevant context, you save GPU cycles and memory without losing accuracy. For the crypto-adjacent compute market, this means cheaper inference costs and faster response times. While regulators sleep, researchers are actually optimizing the engine. Stop waiting for moonshots and start optimizing your latency. Efficiency is the only alpha that doesn't rug.