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

# Audio-to-LLM

> Run your own prompts on a pre-recorded transcript with an LLM - summaries, Q&A, extraction, and more.

<Badge color="blue" size="lg" icon="file-audio">
  Pre-recorded
</Badge>

**Audio-to-LLM** runs once the transcription is generated. You provide **one or more prompts**; each prompt is executed against the **transcript text** from the same job using the configured model, yielding **one LLM response per prompt**. Use it to extract action items, answer questions about the recording, or run any text analysis you express in natural language.

Unlike the built-in [Summarization](/chapters/audio-intelligence/summarization) feature — which produces a fixed-format summary — Audio-to-LLM lets you write **your own instructions**: ask for a summary in the exact format, tone, and level of detail your product needs, or combine a summary with other analyses (action items, compliance checks) in a single request.

## Usage

1. Include `audio_to_llm: true` and an `audio_to_llm_config` object (at minimum, a `prompts` array) in your [pre-recorded transcription request](/chapters/pre-recorded-stt/quickstart).
2. Gladia transcribes the audio, along with any other audio-intelligence options you enabled on that request.
3. Each prompt is run on the resulting transcript via the LLM.
4. The API returns **one result object per prompt** (same order as `prompts`), each containing the original `prompt` and the model `response`.

<Note>
  Audio-to-LLM sends **plain transcript text** to the model. Raw audio and other fields from the transcription response are **not** added to the LLM prompt context.
</Note>

## Model selection

By default the model used to execute your prompts is **[GPT 5.4 Nano](https://openrouter.ai/openai/gpt-5.4-nano)** (`openai/gpt-5.4-nano`), a fast option suited to high-volume summaries and extraction. The `model` can be customized when you need stronger reasoning, richer analysis, longer outputs, or behavior that fits a specific model.

You can use **any model listed on [OpenRouter](https://openrouter.ai/models)** by setting the `model` key. Prices reflect the public OpenRouter rate plus a platform fee added by Gladia.

## Example

A single prompt is enough to get started (you can omit `model` to use the default):

```json Pre-recorded theme={"system"}
{
  "audio_to_llm": true,
  "audio_to_llm_config": {
    "prompts": [
      "Summarize the transcript in three bullet points."
    ]
  }
}
```

Example response shape for one prompt:

```json Pre-recorded theme={"system"}
{
  "success": true,
  "is_empty": false,
  "results": [
    {
      "success": true,
      "is_empty": false,
      "results": {
        "prompt": "Summarize the transcript in three bullet points.",
        "response": "- Intro and context\n- Main discussion\n- Conclusion and next steps"
      },
      "exec_time": 1.4122809978485107,
      "error": null
    }
  ],
  "exec_time": 4.521103805541992,
  "error": null
}
```

## Example: post-meeting workflow

For a **post-meeting** pass, you might ask for bullet takeaways, a short summary, and follow-up actions for the next meeting:

```json Pre-recorded theme={"system"}
{
  "audio_to_llm": true,
  "audio_to_llm_config": {
    "model": "openai/gpt-5.4",
    "prompts": [
      "Summarize the meeting as bullet points: main topics, decisions, and open questions.",
      "Give a concise paragraph summarizing what this meeting was about and the outcome.",
      "List action items and follow-ups to prepare for the next meeting; include owners if they were mentioned."
    ]
  }
}
```

With this configuration, your output might look like this:

```json Pre-recorded theme={"system"}
{
  "success": true,
  "is_empty": false,
  "results": [
    {
      "success": true,
      "is_empty": false,
      "results": {
        "prompt": "Summarize the meeting as bullet points: main topics, decisions, and open questions.",
        "response": "- **Roadmap Q2**: Team aligned on shipping the billing integration first.\n- **Decision**: Weekly sync moved to Tuesday.\n- **Open question**: Whether to support SSO in v1 is still TBD."
      },
      "exec_time": 1.7726809978485107,
      "error": null
    },
    {
      "success": true,
      "is_empty": false,
      "results": {
        "prompt": "Give a concise paragraph summarizing what this meeting was about and the outcome.",
        "response": "The group reviewed Q2 priorities, agreed to prioritize billing, and rescheduled the standing meeting. SSO scope was left for a follow-up once design signs off."
      },
      "exec_time": 1.5122809978485107,
      "error": null
    },
    {
      "success": true,
      "is_empty": false,
      "results": {
        "prompt": "List action items and follow-ups to prepare for the next meeting; include owners if they were mentioned.",
        "response": "- **Alex**: Finalize SSO requirements doc by Friday.\n- **Jamie**: Share billing API cutover checklist with the team.\n- **Everyone**: Review the updated roadmap draft before next sync."
      },
      "exec_time": 1.8932809978258485,
      "error": null
    }
  ],
  "exec_time": 6.267103805541992,
  "error": null
}
```

## Response shape

* Top-level `results` is an **array** with **one entry per prompt**, in the **same order** as `audio_to_llm_config.prompts`.
* Each entry includes `success`, optional `error`, timing fields, and nested `results.prompt` / `results.response` with the LLM output for that prompt.

## Pricing

The input provided to the LLM is the full transcription. All prices are per 1M tokens and include platform fees.

| Model                                                                                 | `model` config                  | Context Window | Input  | Output  |
| ------------------------------------------------------------------------------------- | ------------------------------- | -------------- | ------ | ------- |
| [OpenAI: GPT-5.4 Nano](https://openrouter.ai/openai/gpt-5.4-nano)                     | `openai/gpt-5.4-nano`           | 400k           | \$0.26 | \$1.76  |
| [OpenAI: GPT-5.4](https://openrouter.ai/openai/gpt-5.4)                               | `openai/gpt-5.4`                | 1.1M           | \$3.25 | \$19.50 |
| [Anthropic: Claude Opus 4.7](https://openrouter.ai/anthropic/claude-opus-4.7)         | `anthropic/claude-opus-4.7`     | 1M             | \$6.50 | \$32.50 |
| [Google: Gemini 3.1 Pro Preview](https://openrouter.ai/google/gemini-3.1-pro-preview) | `google/gemini-3.1-pro-preview` | 1M             | \$2.60 | \$15.60 |
| [xAI: Grok 4.20](https://openrouter.ai/x-ai/grok-4.20)                                | `x-ai/grok-4.20`                | 2M             | \$2.60 | \$7.80  |
| [Meta: Llama 4 Maverick](https://openrouter.ai/meta-llama/llama-4-maverick)           | `meta-llama/llama-4-maverick`   | 1M             | \$0.20 | \$0.78  |