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.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
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
What does one inference request cover, and what counts as a single request for billing?
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.
How do the host-hour charge and the per-request charge combine on my bill?
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.
Am I charged host hours when the ml.m5.large instance is not running inference?
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.
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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:
Real-time inference
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 .
Batch transform
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.
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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.
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.
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.
A voice AI platform delivering real-time Text-to-Speech, Speech-to-Text, and instant voice cloning through streaming WebSocket APIs. Build low-latency voice agents in English, French, German, Spanish, and Portuguese with a single API key.
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