Atlas / Models / OpenAI / OpenAI: GPT Audio

OpenAI: GPT Audio✓ Catalog verified

openai/gpt-audio

The gpt-audio model is OpenAI's first generally available audio model. The new snapshot features an upgraded decoder for more natural sounding voices and maintains better voice consistency. Audio is priced...

Input price
$2.50 /1M
Output price
$10.00 /1M
Context
128K
Modalities
textaudio
Released
Jan 19, 2026
Tool calling
✓ Yes
Atlas signal
84/100
01

Overview

The gpt-audio model is OpenAI's first generally available audio model. The new snapshot features an upgraded decoder for more natural sounding voices and maintains better voice consistency. Audio is priced...

Access: available through the official OpenAI API. Context window: 128K.

Pricing and metadata from the ModelsAtlas catalog.Last refreshed Sep 19, 2026
02

Specifications

API identifieropenai/gpt-audio
ProviderOpenAI
Model typeMultimodal LLM
Context window128K catalog
Input modalitiestext · audio
Output modalitiestext · audio
ReleasedJan 19, 2026
TokenizerGPT
ModeratedYes
Architecture modalitytext+audio->text+audio
Supported parameters
frequency_penaltylogit_biaslogprobsmax_tokenspresence_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_logprobstop_p
Source: provider documentation + catalog feedMethodology →

API defaults

Default parameters
{
  "top_k": null,
  "top_p": null,
  "temperature": null,
  "presence_penalty": null,
  "frequency_penalty": null,
  "repetition_penalty": null
}
03

Pricing

Live pricing components for openai/gpt-audio as published in the catalog.

$2.50
Input /1M
$10.00
Output /1M
Per request
Per image
Pricing componentRaw unit priceNormalizedUnit
Prompt tokens$0.0000025$2.50 / 1MPer input token
Completion tokens$0.00001$10.00 / 1MPer output token
Request feeN/AN/APer request
Image feeN/AN/APer image unit
Web search feeN/AN/APer search request
Source: catalog pricing feedCompare all pricing →Cheapest models →
04

Cost calculator

Estimate monthly spend from your own token volumes.

Scale / Volume

Estimated Total Cost

$3.25Calculated from current list pricing in the ModelsAtlas catalog.
05

Capabilities

CapabilityStatusWhat it means
Visual UnderstandingNot advertisedImage and document analysis support
Audio Processing✓ SupportedSpeech and voice aligned flows
Tool Calling✓ SupportedSupports tools / function calling
Self-HostingNot advertisedDeploy outside managed APIs
Derived from catalog capability tags and supported parameters
06

Capability signals

Directional signals derived from model metadata and capability tags — not official benchmark submissions.

OpenAI: GPT Audio
MMLU Signal (Reasoning)
79signal
Coding Signal (HumanEval proxy)
97signal
Math Signal (GSM8K proxy)
79signal
Science Signal (GPQA proxy)
79signal
Estimated from metadata — not an official benchmark runAll benchmarks →Methodology →
07

Quick start

Call OpenAI: GPT Audio through an OpenAI-compatible client.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="openai/gpt-audio",
    messages=[{"role": "user", "content": "Explain quantum physics."}]
)

print(response.choices[0].message.content)
08

Alternatives

Closest models by context window from a different provider.

09

Sources & attribution

Pricing and metadata are maintained in the ModelsAtlas catalog.

Capability bars use metadata tags — directional estimates onlyHow we source and verify data →
10

Frequently asked questions

How much does OpenAI: GPT Audio cost?

$2.50 per 1M input tokens and $10.00 per 1M output tokens on the official OpenAI API.

What is the context window of OpenAI: GPT Audio?

OpenAI: GPT Audio supports up to 128K tokens of context.

Does OpenAI: GPT Audio support tool / function calling?

Yes, OpenAI: GPT Audio supports tool / function calling — you can register tools and the model will emit structured tool calls.

How do I access OpenAI: GPT Audio?

Use the official OpenAI API with the model id `openai/gpt-audio`. See the Quick start section above for code examples.