Context Window
128,000
Tokens
Model Cost Profile
OpenAI: GPT Audio
Developer: openai
Pricing updated Mar 11, 2026
Input rank: #292Output rank: #283
OpenAI's GPT Audio model is designed for applications requiring extensive audio processing, making it ideal for voice recognition, transcription services, and conversational AI. With a context window of 128,000 tokens, this model enables teams to handle long-form audio inputs, enhancing the accuracy and relevance of generated responses. The pricing structure, at $2.50 per million input tokens and $10.00 per million output tokens, allows teams to budget effectively based on their specific usage needs and project scales.
📋 Structured Output
Input Price / 1M
$2.50
Prompt tokens
Output Price / 1M
$10.00
Completion tokens
Intelligence (MMLU)
Benchmark Pending
Massive Multitask Language Understanding
Side-by-Side Pricing Table
| Usage Type | Price / 1M Tokens |
|---|---|
| Input (Prompt) | $2.50 |
| Output (Completion) | $10.00 |
Price History
OpenAI: GPT Audio Pricing Trend
Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 — Mar 11
Current Input / 1M
$2.50
Current Output / 1M
$10.00
Cost Calculator
Estimate monthly spend for OpenAI: GPT Audio based on your workload.
01.0B
0500M
Estimated Monthly Cost
$183
25M input + 12M output tokens
Cheaper Alternatives to Compare
Quick links for cost-down decisions before production rollout.
FAQ
Common pricing and benchmark questions for OpenAI: GPT Audio.
How much does OpenAI: GPT Audio cost per 1M input tokens?
OpenAI: GPT Audio input pricing is $2.50 per 1M tokens based on the latest synced provider data.
How much does OpenAI: GPT Audio cost per 1M output tokens?
OpenAI: GPT Audio output pricing is $10.00 per 1M tokens based on the latest synced provider data.
What context window does OpenAI: GPT Audio support?
OpenAI: GPT Audio supports a context window of 128,000 tokens.
How can I compare OpenAI: GPT Audio with cheaper alternatives?
Use the comparison links on this page to open direct model-vs-model pricing and benchmark pages, then evaluate monthly spend projections for your workload.