# Liquid AI D1-Ultra

> Source: <https://www.liquid.ai/blog/d1-ultra>
> Published: 2026-10-15 17:15:43+00:00

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# d1-ultra: Introducing the World’s Best Decision Model

Today, we release d1-ultra, our new multimodal **decision model with state-of-the-art performance**. Most decision models work well on easy and common tasks. We built d1-ultra for harder, messier real-world use cases, like spotting a defect on a circuit board against its spec or checking a damage claim against the customer’s photo.

d1-ultra is available today on the [Liquid API](https://console.liquid.ai/) at $0.042 per million input tokens.

[Try on Liquid Console](https://console.liquid.ai/)

[Try on d1 Playground](https://d1.liquid.ai/)

## What d1-ultra does

d1-ultra answers the same three question types as d1:

- **noul** : a yes/no question, answered with a probability from 0 to 1.
- **Choice** : one label from many, with a probability per label.
- **Score** : a position on a scale.

## Results

Compared to d1, we based d1-ultra on a larger open-weight model with a series of Liquid-specific heavy customizations. It provides significant gains when combined with our training pipeline, especially on knowledge-related tasks.

We compared it to our previous model d1 and Jev 1.14 across 112 unique evaluations.

Accuracy is not enough: decision models also output probabilities that must be properly calibrated. We realized that most decision models are overconfident in their responses. That’s why we specifically trained d1-ultra to produce more reliable probabilities.

d1-ultra outperforms Jev 1.14 across all tasks, delivering better-calibrated answers and higher accuracy at the same price. To see how it works in practice, you can find more demos running on d1-ultra in the [d1 Playground](http://d1.liquid.ai/).

d1-ultra also outperforms all other decision models [Artificial Analysis Decision Index](https://artificialanalysis.ai/evaluations/artificial-analysis-decision-index) by at least 8 points."

## Availability and Pricing

d1-ultra is available on the [Liquid AI API](http://console.liquid.ai/). Create your API key and start building today. d1-ultra will soon be available through [Vercel](https://vercel.com/ai-gateway/models/d1) and [OpenRouter](https://openrouter.ai/liquid/d1).

The model reads text, images, or both at the same time, like in this example:

``` python
import base64, os, requests

image = base64.b64encode(open("board.jpg", "rb").read()).decode()

response = requests.post(
    "https://api.liquid.ai/decisions/v1/systemone",
    headers={"Authorization": f"Bearer {os.environ['LIQUID_API_KEY']}"},
    json={
        "model": "d1-ultra",
        "images": [f"data:image/jpeg;base64,{image}"],
        "state": "Camera image of a circuit board on the production line.",
        "questions": 
            {"defect": {
                "type": "noul", 
                "instructions": "Does this circuit board have a defect?"
             }
         },
    },
)

print(response.json()["answers"]["defect"]["noul"])
```

The full API reference is in the [decision models documentation](https://docs.liquid.ai/lfm/models/decision-models).

d1-ultra is billed on input tokens only, with no output tokens. Images are counted as input tokens at the same rate as text: 1.5 tokens per 32×32-pixel patch, so a 1024×1024 image costs 1,536 tokens. Each question is billed as its own prompt, including its text and all images.

d1-ultra is our most capable decision model so far. We’re committed to continuing our work on decision models across a range of sizes, with new features, higher decision quality, and lower latency, and we plan to provide regular updates.

[Try on Liquid Console](https://console.liquid.ai/)

[Read our docs](https://docs.liquid.ai/lfm/models/decision-models)

## **Citation**

For citations, please use the following reference or BibTeX:
