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    Gradium real-time TTS (per request)

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    Sold by: Gradium 
    Deployed on AWS
    Gradium builds the technological backbone, models and infrastructure, to support all voice applications. We work at the finest level of details to design natural, expressive, real-time voice interactions at scale.

    Overview

    We provide real-time Text to Speech and Speech to Text models in English, French, German, Spanish and Portuguese, instant voice cloning and much more.

    Highlights

    • Real time
    • Highly expressive
    • 5 languages

    Details

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    Delivery method

    Latest version

    Deployed on AWS
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    Pricing

    Gradium real-time TTS (per request)

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    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (2)

     Info
    Dimension
    Description
    Cost
    ml.m5.large Inference (Batch)
    Recommended
    Model inference on the ml.m5.large instance type, batch mode
    $0.00/host/hour
    inference.count.m.i.c Inference Pricing
    inference.count.m.i.c Inference Pricing
    $0.006/request

    AI Insights

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    Dimensions summary

    This listing bills on usage, with two separate dimensions. You pay per hour for model inference running on the ml.m5.large instance in batch mode, charged by host hours. You also pay per inference request under the request-based dimension. The two charges work independently: one covers the compute time the model runs, the other counts the number of inference calls you make. Costs rise as you add host hours or make more requests. There are no upfront commitments or fixed tiers here; your total scales directly with how much you run and call.

    Top-of-mind questions for buyers

    A request is one call to the text-to-speech model. Each session can run up to 300 seconds, so longer text should be split into separate sessions. You pay per request you submit, regardless of audio length within that session limit.
    The two charges bill independently and both appear together. The host-hour charge meters time the ml.m5.large instance runs in batch mode. The per-request charge counts each inference call. Host hours drive cost for long-running compute; request volume drives cost when you make many calls.
    The host-hour charge meters time the instance runs in batch mode. When the instance is stopped, software host-hour charges stop too. Underlying AWS storage or related fees may still apply separately. The per-request charge applies only when you submit inference calls.
    gradium.ai
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    No refund policy

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    Vendor terms and conditions

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    Usage information

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    Delivery details

    Amazon SageMaker model

    An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.

    Deploy the model on Amazon SageMaker AI using the following options:
    Deploy the model as an API endpoint for your applications. When you send data to the endpoint, SageMaker processes it and returns results by API response. The endpoint runs continuously until you delete it. You're billed for software and SageMaker infrastructure costs while the endpoint runs. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Deploy models for real-time inference  .
    Deploy the model to process batches of data stored in Amazon Simple Storage Service (Amazon S3). SageMaker runs the job, processes your data, and returns results to Amazon S3. When complete, SageMaker stops the model. You're billed for software and SageMaker infrastructure costs only during the batch job. Duration depends on your model, instance type, and dataset size. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Batch transform for inference with Amazon SageMaker AI  .
    Version release notes

    Validated Gradium real-time text-to-speech model update.

    Additional details

    Inputs

    Summary

    Bidirectional streaming for real-time inference

    Input MIME type
    application/json, application/octet-stream
    {"type":"text","text":"foo"}
    Not applicable

    Resources

    Vendor resources

    Support

    Vendor support

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

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