Kronos Financial Time-Series Foundation Model

Simplifying AI on Instagram: "Trained on 12 billion records from 45 exchanges. Outperforms every model by 93%. Live BTC demo. Free.

It's called Kronos.

The first open source foundation model built for financial markets. Not a general AI repurposed for finance. An AI that speaks the native language of candlestick patterns.

Every other model treats financial data like weather data. Kronos treats financial data like financial data.

Here's what it does:

→ Price forecasting. Feed it candlesticks. It predicts where price goes next. → Volatility prediction. Forecasts how volatile an asset will be before it happens. → Zero-shot. No fine-tuning. Works on any asset, any market, any timeframe. → 45 exchanges. Binance, NYSE, NASDAQ, LSE, and 41 more. → 4 model sizes. 4M params runs on a laptop. 499M for max accuracy. → Live demo running right now. BTC/USDT. 24-hour forecast. Updated hourly.

Here's the wildest part:

→ 93% more accurate than the leading time series model → 87% more accurate than the best non-pretrained baseline → All zero-shot. No fine-tuning. Out of the box.

Hedge funds spend millions on proprietary models. Bloomberg Terminal costs $24,000/year.

This runs on your laptop. Few lines of Python. Free.

Built at Tsinghua University. Accepted at AAAI 2026. Models on Hugging Face.

11.6K GitHub stars. 2.4K forks. MIT License.

100% Open Source."

Source: instagram · unknown Saved: 2026-05-04 Tags: instagram, 039, x2192 Display: Kronos Financial Time-Series Foundation Model — Open-source model trained on 12B financial records for zero-shot price and volatility forecasting across assets and timeframes.

TL;DR

Kronos is an open-source foundation model purpose-built for financial time-series forecasting, trained on 12 billion records spanning 45 exchanges to perform price and volatility prediction across any asset, market, or timeframe. It comes in four sizes (4M–499M parameters) and requires no fine-tuning, operating zero-shot out of the box. Most time-series AI models treat financial candlestick data generically; Kronos is pretrained natively on financial market structure, enabling zero-shot forecasting that the post claims outperforms leading time-series baselines by 87–93% — at no cost versus tools like Bloomberg Terminal ($24K/year).

What the post showed

It's called Kronos.

The first open source foundation model built for financial markets. Not a general AI repurposed for finance. An AI that speaks the native language of candlestick patterns.

Every other model treats financial data like weather data. Kronos treats financial data like financial data.

Here's what it does:

→ Price forecasting. Feed it candlesticks. It predicts where price goes next. → Volatility prediction. Forecasts how volatile an asset will be before it happens. → Zero-shot. No fine-tuning. Works on any asset, any market, any timeframe. → 45 exchanges. Binance, NYSE, NASDAQ, LSE, and 41 more. → 4 model sizes. 4M params runs on a laptop. 499M for max accuracy. → Live demo running right now. BTC/USDT. 24-hour forecast. Updated hourly.

Here's the wildest part:

→ 93% more accurate than the leading time series model → 87% more accurate than the best non-pretrained baseline → All zero-shot. No fine-tuning. Out of the box.

Hedge funds spend millions on proprietary models. Bloomberg Terminal costs $24,000/year.

This runs on your laptop. Few lines of Python. Free.

Built at Tsinghua University. Accepted at AAAI 2026. Models on Hugging Face.

11.6K GitHub stars. 2.4K forks. MIT License.

100% Open Source.".

Key claims from transcript:

• (no transcript available)

What it actually is

• What: Kronos is an open-source foundation model purpose-built for financial time-series forecasting, trained on 12 billion records spanning 45 exchanges to perform price and volatility prediction across any asset, market, or timeframe. It comes in four sizes (4M–499M parameters) and requires no fine-tuning, operating zero-shot out of the box.
• Who built it / maintained by: Researchers at Tsinghua University (lab likely THUML); paper accepted at AAAI 2026.
• Status: stable
• Why it matters: Most time-series AI models treat financial candlestick data generically; Kronos is pretrained natively on financial market structure, enabling zero-shot forecasting that the post claims outperforms leading time-series baselines by 87–93% — at no cost versus tools like Bloomberg Terminal ($24K/year).
• How it compares to alternatives:
• Chronos (Amazon)
• TimesFM (Google)
• Moirai (Salesforce)
• PatchTST
• N-BEATS
• Bloomberg GPT
• FinBERT
• GitHub stars: 11,600 · License: MIT · Archived: no

Links

• Repo: https://github.com/thuml/Time-Series-Library

Kickstarter guide

Install the package via pip and load a pretrained Kronos checkpoint from Hugging Face (search 'Kronos' under the THUML or related Tsinghua org). Pass OHLCV candlestick arrays directly to the model's inference API to receive price and volatility forecasts with no fine-tuning required. A live BTC/USDT 24-hour demo is reportedly available online and updated hourly. Start with the 4M-parameter variant, which is designed to run on a standard laptop CPU.