gpt-4o-mini-tts
Version: 2025-12-15
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Key capabilities
About this model
The gpt-4o-mini-tts model is an advanced text-to-speech solution designed to convert written text into natural-sounding speech. Leveraging the capabilities of GPT-4o, this model offers customizable voice output, allowing developers to instruct the model to speak in specific ways, such as "talk like a sympathetic customer service agent."Key model capabilities
- Customizable voice output with the ability to instruct the model to speak in specific ways
- Natural-sounding speech generation ideal for audiobooks, podcasts, and interactive voice agents
- Expressive and dynamic voice generation capabilities
- Processing of substantial text inputs with support for up to 2,000 tokens
Use cases
See Responsible AI for additional considerations for responsible use.Key use cases
- Customer Service Automation: gpt-4o-mini-tts can be integrated into customer service systems to provide dynamic and empathetic voice responses. By instructing the model to speak in specific ways, such as "talk like a sympathetic customer service agent," businesses can enhance customer interactions and improve satisfaction.
- Content Creation and Publishing: The model is ideal for converting written content into engaging audio formats. This can be particularly useful for creating audiobooks, podcasts, and other spoken content, allowing creators to reach a broader audience and cater to different consumer preferences.
- Accessibility Enhancements: gpt-4o-mini-tts can be used to make digital content more accessible to individuals with visual impairments or reading difficulties. By converting text into natural-sounding speech, the model helps ensure that information is available to everyone, promoting inclusivity.
Out of scope use cases
Our models are not specifically designed or evaluated for all downstream purposes. Developers should consider common limitations of language models as they select use cases, and evaluate and mitigate for accuracy, safety, and fairness before using within a specific downstream use case, particularly for high-risk scenarios. Developers should be aware of and adhere to applicable laws or regulations (including privacy, trade compliance laws, etc.) that are relevant to their use case.Pricing
Pricing is based on a number of factors, including deployment type and tokens used. See pricing details here.Technical specs
The provider has not supplied this information.Training cut-off date
The provider has not supplied this information.Training time
The provider has not supplied this information.Input formats
This model supports an input token limit of 2,000 tokens, allowing it to process substantial text inputs effectively.Output formats
The provider has not supplied this information.Supported languages
The provider has not supplied this information.Sample JSON response
The provider has not supplied this information.Model architecture
The provider has not supplied this information.Long context
The provider has not supplied this information.Optimizing model performance
The provider has not supplied this information.Additional assets
The provider has not supplied this information.Training disclosure
Training, testing and validation
gpt-4o-mini-tts has been pretrained on diverse and high-quality text and audio datasets, ensuring a deep understanding of speech nuances and natural intonation. The training process incorporates rigorous enhancement techniques, including supervised fine-tuning and reinforcement learning, to optimize performance and accuracy.Distribution
Distribution channels
This model is provided through the Azure OpenAI Service.More information
The following documents are applicable:Responsible AI considerations
Safety techniques
The provider has not supplied this information.Safety evaluations
The provider has not supplied this information.Known limitations
Our models are not specifically designed or evaluated for all downstream purposes. Developers should consider common limitations of language models as they select use cases, and evaluate and mitigate for accuracy, safety, and fairness before using within a specific downstream use case, particularly for high-risk scenarios. Developers should be aware of and adhere to applicable laws or regulations (including privacy, trade compliance laws, etc.) that are relevant to their use case.Acceptable use
Acceptable use policy
The provider has not supplied this information.Model Specifications
Context Length2000
LicenseCustom
Last UpdatedDecember 2025
Input TypeText,Audio
Output TypeText,Audio
ProviderOpenAI
Languages57 Languages