Mistral AI 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.

All open source here : https://lnkd.in/eJhCTMfk