Open-weight AI is 6–7 months behind the closed frontier but frankly your workload doesn't care. Did your problems get 6–7 months harder? Epoch measured the capability gap specifically for cybersecurity. 🟣 GLM-5.3 → 160 Cyber ECI 🟦 GPT-5.4 from March → 157 🟦 today's closed frontier → ~171 So today's best open-weight cyber model is roughly where the closed frontier was 6–7 months ago. That sounds like bad news for Local AI. I'm not sure it is. Because there's a more fundamental question - Did your problems get 6–7 months harder? If yesterday's frontier model can already 💻 build the app you need 📄 search your documents 🔧 fix your code 📊 analyze your spreadsheet 🤖 automate your workflow then today's smarter frontier model doesn't suddenly make yesterday's model incapable. This is the part of AI benchmarks I think we're beginning to miss. The frontier keeps moving. But the capability threshold required to solve problems nearly all of us encounter often doesn't. Once a local model crosses that threshold, the competition changes. Most people don't actually want to code. They want the thing the code produces. If a local model can write the tool, run it and solve the problem, it doesn't necessarily matter that Opus can solve a substantially harder problem. And today's other OpenRouter number makes this point 👉 Open weights → 72% of tokens / 27% of spend. ⚠️ Epoch measured cybersecurity capability, not general everyday usefulness, and GLM-5.3's Cyber ECI currently comes from only three benchmark results. Epoch AI Link in ALT