---
title: Energy Tracking
description: Deterministic compute-intensity coefficients for carbon-aware AI operations, with energy caps and per-model coefficients.
---

The harness tracks energy consumption using deterministic compute-intensity coefficients. This provides a proxy for carbon impact without requiring real-time power measurement.

## Energy Formula

```
energy_units = coefficient * (input_tokens + output_tokens * 1.5)
```

Output tokens are weighted 1.5x because generation is more compute-intensive than prompt processing.

## Energy Coefficients

| Model | Coefficient | Relative Cost |
|---|---|---|
| gpt-3.5-turbo | 0.20 | Lowest |
| gemini-1.5-flash | 0.20 | Lowest |
| gemini-2.0-flash | 0.25 | Very low |
| claude-haiku-3.5 | 0.30 | Low |
| gemini-2.5-flash | 0.30 | Low |
| gpt-4o-mini | 0.30 | Low |
| gpt-5-mini | 0.35 | Low |
| o3-mini | 0.50 | Medium |
| o1-mini | 0.80 | Medium-high |
| gpt-4o | 1.00 | Baseline |
| claude-sonnet-4 | 1.00 | Baseline |
| gemini-1.5-pro | 1.00 | Baseline |
| gpt-5 | 1.20 | High |
| gemini-2.5-pro | 1.20 | High |
| gpt-4-turbo | 1.50 | High |
| gpt-4 | 1.50 | High |
| claude-opus-4.5 | 1.80 | Very high |
| o1 | 2.00 | Highest |

## Energy Caps

Set a maximum energy budget for a run:

```python
import cascadeflow

cascadeflow.init(mode="enforce")

with cascadeflow.run(max_energy=100.0) as session:
    result = await agent.run("Process this large dataset")

    summary = session.summary()
    print(f"Energy used: {summary['energy_used']:.1f} units")
```

When energy exceeds the cap:
- In `observe` mode: logged but not enforced
- In `enforce` mode: execution stops with `action: "stop"`

## Energy-Aware KPI Weights

Include energy in KPI weights for carbon-aware routing:

```python
with cascadeflow.run(
    kpi_weights={"quality": 0.4, "cost": 0.3, "energy": 0.3}
) as session:
    # Routes toward lower-energy models when quality allows
    result = await agent.run("Summarize this article")
```

## Pricing Table

Full pricing for all 18 supported models (USD per 1M tokens):

| Model | Input | Output |
|---|---|---|
| **OpenAI** | | |
| gpt-4o | $2.50 | $10.00 |
| gpt-4o-mini | $0.15 | $0.60 |
| gpt-5 | $1.25 | $10.00 |
| gpt-5-mini | $0.20 | $0.80 |
| gpt-4-turbo | $10.00 | $30.00 |
| gpt-4 | $30.00 | $60.00 |
| gpt-3.5-turbo | $0.50 | $1.50 |
| o1 | $15.00 | $60.00 |
| o1-mini | $3.00 | $12.00 |
| o3-mini | $1.10 | $4.40 |
| **Anthropic** | | |
| claude-sonnet-4 | $3.00 | $15.00 |
| claude-haiku-3.5 | $1.00 | $5.00 |
| claude-opus-4.5 | $5.00 | $25.00 |
| **Google** | | |
| gemini-2.5-flash | $0.15 | $0.60 |
| gemini-2.5-pro | $1.25 | $10.00 |
| gemini-2.0-flash | $0.10 | $0.40 |
| gemini-1.5-flash | $0.075 | $0.30 |
| gemini-1.5-pro | $1.25 | $5.00 |

<Tip>
**Example walkthrough:** [KPI-Weighted Routing (energy profile)](/examples/kpi-weighted-routing) | **GitHub:** [examples/cost_tracking.py](https://github.com/lemony-ai/cascadeflow/blob/main/examples/cost_tracking.py)
</Tip>
