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Kronos Small

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NeoQuasar/Kronos-small

24.7M params | 512 context | $0.00025 per forecast | MIT

Kronos Small is the mid-size checkpoint in the NeoQuasar Kronos family, sitting between the lightweight Mini variant and the higher-capacity Base model. It is the natural step up when Kronos Mini leaves accuracy on the table but the full Base checkpoint is more than a workload needs.

It uses a larger tokenizer vocabulary and more transformer capacity than the Mini variant, which is what improves accuracy on complex multi-asset financial forecasting tasks while keeping the same overall design — a GPT-style decoder over tokens produced by the family's financial candlestick tokenizer. Like the rest of the family it is designed for OHLCV candlestick data; the official examples require at least OHLC columns, with volume and amount remaining optional. The official Kronos model cards describe pretraining on over 12B K-line records from 45 global exchanges.

On TSFM.ai reach for Kronos Small as the balanced option for financial candlestick forecasting: stronger than Kronos Mini on complex multi-asset tasks, cheaper than Kronos Base. Drop to Mini when serving cost or throughput dominates, or step up to Base when maximum forecast quality is the priority.

Model Classification

Family

Kronos

Type

time series foundation model

Pretrained time-series model exposed on TSFM.ai for zero-shot or few-shot forecasting workloads.

Training Data

Official Kronos model cards describe pretraining on over 12B K-line records from 45 global exchanges.

Recommended For

  • Financial time-series forecasting with OHLCV candlestick data
  • Multi-asset price prediction across equities, forex, and crypto

Strengths

  • Purpose-built tokenizer for financial price movement patterns
  • Native OHLCV support with synthetic fallback for univariate series

Limitations

  • Domain-specific to financial data — not a general-purpose TSFM
  • Best fit when open, high, low, and close covariates are provided explicitly; the univariate fallback is a compatibility path, not the ideal contract
  • Limited public documentation and benchmark coverage compared to major TSFM families

Capabilities

forecastingzero-shot

Tags

neoquasarkronosfinancialohlcv

Specifications

Parameters
24.7M
Architecture
GPT-style decoder with financial candlestick tokenizer
Context length
512
Max context
512
Minimum history
n/a
Recommended history
n/a
Input step
n/a
Required target series
1
Temperature
Supported
Top P
Supported
Max output
1,024
Avg latency
n/a
Uptime
n/a
Plan limits
1,000 rpm free · 1,000,000 rpm with billing
Accelerator
T4
Regions
Virginia, US
License
MIT

Pricing

Per forecast
$0.00025

Performance

Average latency
n/a
Availability
n/a
Plan limits
1,000 rpm free · 1,000,000 rpm with billing

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