Mistral recently released a 209M model that can predict future data locally on a CPU in ~140 milliseconds. Not every useful AI model needs to talk (just like Jev) No GPU required. It's a super small foundation model designed for time-series forecasting. Give it historical data like: 📈 sales ⚡ power usage 🏭 sensor readings 📦 demand/inventory 🌡️ telemetry …and it predicts what comes next without training a new model for each dataset. The largest version stats 🧠 209M parameters 💾 837MB FP32 🖥️ runs on CPU or GPU 📚 up to 32,768 historical time steps 🔮 forecasts up to 1,024 steps per forward pass 📊 outputs 21 probability quantiles 🎯 Mistral says it ranks #1# among pretrained/zero-shot models on all three major public forecasting benchmarks 🥇 GIFT-Eval 🥇 TIME 🥇 fev-bench It can get small like Timestral-5M → 21MB Mistral says on an 8-thread CPU: ⚡ 5M model → ~10 ms ⚡ 209M model → ~140 ms for a one-day forecast from three weeks of 15-minute data. 🔗 Links below in ALT.