# Liquid d1 Ultra

Liquid d1-ultra is a multimodal decision model for classification, routing, and scoring across text and images, with a 32,768-token context window. It returns calibrated probabilities for yes/no, multiple-choice, and scale-based questions in a single forward pass without generating output tokens. It is designed for demanding real-world tasks such as visual defect inspection and evaluating damage claims against customer photos.

- **Model ID:** `liquid/d1-ultra`
- **Type:** evaluation
- **Providers:** liquid
- **Context window:** 32,768
- **Maximum output tokens:** 0
- **Pricing:** $0.042/1M input tokens
- **Canonical page:** https://vercel.com/ai-gateway/models/d1-ultra

## Supported parameters

Detailed capability metadata has not been reported for this model.

## Example

```ts
import { experimental_decide as decide } from 'ai';

const result = await decide({
  model: 'liquid/d1-ultra',
  state: 'The support agent issued a full refund to the customer.',
  questions: {
    refunded: {
      type: 'boolean',
      instructions: 'Was a refund issued?',
    },
  },
})
```

## Links

- [Model page](https://vercel.com/ai-gateway/models/d1-ultra)
- [AI Gateway documentation](https://vercel.com/docs/ai-gateway)
- [Provider model documentation](https://www.liquid.ai/blog/d1-ultra)
- [Provider pricing](https://www.liquid.ai/blog/d1-ultra)