> ## Documentation Index
> Fetch the complete documentation index at: https://docs.runanywhere.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# generate()

> Full text generation with performance metrics

Generate text with detailed metrics including latency, token count, and generation speed.

```dart theme={null}
final result = await RunAnywhere.generate(
  'Explain quantum computing in simple terms',
  options: LLMGenerationOptions(
    maxTokens: 200,
    temperature: 0.7,
  ),
);

print('Response: ${result.text}');
print('Tokens: ${result.tokensUsed}');
print('Speed: ${result.tokensPerSecond.toStringAsFixed(1)} tok/s');
print('Latency: ${result.latencyMs.toStringAsFixed(0)}ms');
```

## LLMGenerationOptions

| Parameter       | Type           | Default | Description                |
| --------------- | -------------- | ------- | -------------------------- |
| `maxTokens`     | `int`          | 100     | Maximum tokens to generate |
| `temperature`   | `double`       | 0.8     | Randomness (0.0–2.0)       |
| `topP`          | `double`       | 1.0     | Nucleus sampling parameter |
| `stopSequences` | `List<String>` | `[]`    | Stop generation at these   |
| `systemPrompt`  | `String?`      | `null`  | System prompt for context  |

```dart theme={null}
const options = LLMGenerationOptions(
  maxTokens: 256,
  temperature: 0.7,
  topP: 0.95,
  stopSequences: ['END', '###'],
  systemPrompt: 'You are a helpful coding assistant.',
);
```

## LLMGenerationResult

| Property             | Type      | Description                     |
| -------------------- | --------- | ------------------------------- |
| `text`               | `String`  | Generated text                  |
| `thinkingContent`    | `String?` | Thinking content (if supported) |
| `inputTokens`        | `int`     | Number of input tokens          |
| `tokensUsed`         | `int`     | Number of output tokens         |
| `modelUsed`          | `String`  | Model ID used                   |
| `latencyMs`          | `double`  | Total latency in milliseconds   |
| `tokensPerSecond`    | `double`  | Generation speed                |
| `timeToFirstTokenMs` | `double?` | Time to first token             |

## Thinking Models

Some models support "thinking" tokens for chain-of-thought reasoning:

```dart theme={null}
LlamaCpp.addModel(
  id: 'qwen-cot',
  name: 'Qwen CoT',
  url: '...',
  supportsThinking: true,  // Enable thinking token parsing
);

final result = await RunAnywhere.generate('Solve: 2x + 5 = 15');

if (result.thinkingContent != null) {
  print('Reasoning: ${result.thinkingContent}');
}
print('Answer: ${result.text}');
```

## See Also

<CardGroup cols={2}>
  <Card title="chat()" icon="comments" href="/flutter/llm/chat">
    Simple one-liner
  </Card>

  <Card title="generateStream()" icon="bolt" href="/flutter/llm/stream">
    Stream tokens in real-time
  </Card>
</CardGroup>