Reduce inference costs and increase inference speed by using Multiverse Computing's CompactifAI Mistral Small 3.1 Slim. A 50% compression of the widely known Mistral Small 3.1 model.
Reduce inference costs and increase inference speed by using Multiverse Computing's CompactifAI Mistral Small 3.1 Slim. A 50% compression of the widely known Mistral Small 3.1 model.
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You pay by the host hour for running inference on this compressed language model. Pricing depends on two choices. First, you pick an instance type, which sets the compute hardware. Options range across several g5 sizes plus p4d and p5 GPU instances. Larger instances carry higher hourly rates. Second, you pick an inference mode. Batch mode processes grouped requests, while real-time mode serves live responses. The g5 sizes offer both modes; the p4d and p5 instances offer real-time only. You are billed per hour of use, with no upfront commitment.
Top-of-mind questions for buyers
What does one billed host hour cover for these inference instances?
One host hour covers one hour of a running instance serving this compressed model. The instance type sets the GPU hardware and memory. You are charged per hour the instance runs, regardless of how many requests it processes. Fully stopped instances stop accruing software charges.
How does batch mode billing differ from real-time mode?
Both modes bill per host hour on the same instance. Batch mode processes grouped requests together, so an instance runs only while a job runs. Real-time mode keeps an instance active to serve live responses, accruing charges the whole time it stays up. Batch suits scheduled jobs; real-time suits continuous serving.
Why are some instance types available in real-time mode only?
The p4d and p5 GPU instances are offered for real-time inference only, while the g5 sizes support both batch and real-time. If you need batch processing, choose a g5 instance. For higher-powered real-time serving, the p4d and p5 options are available.
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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
CompactifAI Mistral Small 3.1 Slim inference on a vLLM engine with text-only support
Additional details
Inputs
Outputs
Usage instructions
Sample notebooks
Inputs
Summary
Our model accepts an input compatible with openAI's chat completions endpoint.
Input MIME type
application/json
Real-time inference sample input data
{
"model": "cai-mistral-3-1-small-slim",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Tell me about quantum computing."}
]
}
Batch transform sample input data
{
"model": "cai-mistral-3-1-small-slim",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Tell me about quantum computing."}
]
}
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CompactifAI API empowers organizations with ultra-efficient and scalable AI models that slash compute and energy costs, accelerate deployment, and fuel innovation, all without compromising performance or reliability!
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