Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
Jamba 1.5 Large
By:
Latest Version:
1.0.0
Excels at complex reasoning tasks across all prompt lengths, making it ideal for applications that require high quality outputs.
Product Overview
Jamba 1.5 Large is the first of its kind hybrid Mamba-Transformer architecture at a production grade level offering unmatched efficiency. With an unprecedented context window length (256K), it offers superior quality output for tasks needing large input context & low latency, at a competitive price point for its class.
Key Data
Version
Type
Model Package
Highlights
With a 256K effective long context window, Jamba 1.5 models lead the NVIDIA RULER benchmark—the standard for measuring effective context windows across practical tasks, improving the output quality of key enterprise workflows, such as lengthy document summarization and multi-document analysis.
2.5X faster than leading models in its size class on long context and fastest across all context lengths.
Supports function calling/tool use, structured output (JSON), and grounded generation with citation mode and documents API.
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Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Contact us to request contract pricing for this product.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Model Realtime Inference$60.00/inference
running on any instance
Model Batch Transform$0.00/hr
running on ml.m5.large
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Batch Transform$0.115/host/hr
running on ml.m5.large
Model Batch Transform
For model deployment as Batch transform job in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Batch Transform/hr | |
|---|---|---|
ml.m5.large Vendor Recommended | $0.00 |
Usage Information
Model input and output details
Input
Summary
Jamba 1.5 Large is the first of its kind hybrid Mamba-Transformer architecture at a production grade level offering unmatched efficiency. With an unprecedented context window length (256K), it offers superior quality output for tasks needing large input context & low latency, at a competitive price point for its class.
Input MIME type
application/jsonSample input data
{
"messages": [
{
"role": "user",
"content": "I need help with your product. Can you please assist?"
}
],
"temperature": 1,
"top_p": 1,
"n": 1,
"stop": "\n"
}Output
Summary
See example response here .
Output MIME type
application/jsonSample output data
{
"id": "chat-5361a2113512423d8f3fa5c16cd10bf1",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": " Of course! I'd be happy to help. What product do you need assistance with?"
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 22,
"completion_tokens": 20,
"total_tokens": 42
},
"meta": {
"requestDurationMillis": 369
},
"model": "jamba-1.5-large"
}Sample notebook
Additional Resources
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Support Information
AWS Infrastructure
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