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Available as a NIM, Llama 3.1 8B-Instruct is an 8B-parameter LLM pretrained, instruction tuned model optimized for multilingual dialogue.
Overview
Meta Llama 3.1 is a collection of multilingual large language models (LLMs) that are pre-trained and instruction-tuned generative models.
NVIDIA NIM microservices for Llama 3.1 8B-Instruct simplifies the deployment of the Llama 3.1 8B instruction tuned model which is optimized for language understanding, reasoning, and text generation use cases. Llama 3.1 8B-Instruct is available as an NVIDIA NIM microservice, part of NVIDIA AI Enterprise available on the AWS Marketplace. NIM is a set of easy-to-use microservices designed for secure, reliable deployment of high performance AI model inferencing across clouds, data centers and workstations.
The Llama 3.1 8B-Instruct NIM is a prebuilt container that includes the Meta Llama 3.1 large language model built on inference engines like Triton Inference Server, TensorRT, TensorRT-LLM, and PyTorch. NIM provides features like low latency, high throughput, function calling, metrics export, standard API, optimized profiles & enterprise support.
Highlights
- Llama 3.1 8B-Instruct NIM is an 8-billion-parameter multilingual large language model (LLM) pretrained and instruction tuned generative model. The Llama 3.1 instruction tuned text only model is optimized for multilingual dialogue use cases. It is available as an [NVIDIA NIM microservice](https://docs.nvidia.com/nim/large-language-models/latest/introduction.html).
- NVIDIA NIM, a part of the [NVIDIA AI Enterprise](https://www.nvidia.com/en-us/data-center/products/ai-enterprise/) software platform available on the [AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-ozgjkov6vq3l6), is a set of easy-to-use microservices designed for secure, reliable deployment of high performance AI model inferencing.
Details
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Pricing
Free trial
Try this product free for 90 days according to the free trial terms set by the vendor.
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.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.g5.12xlarge Inference (Batch) Recommended | Model inference on the ml.g5.12xlarge instance type, batch mode | $4.00 |
ml.g5.12xlarge Inference (Real-Time) Recommended | Model inference on the ml.g5.12xlarge instance type, real-time mode | $4.00 |
ml.g5.24xlarge Inference (Batch) | Model inference on the ml.g5.24xlarge instance type, batch mode | $4.00 |
ml.g5.24xlarge Inference (Real-Time) | Model inference on the ml.g5.24xlarge instance type, real-time mode | $4.00 |
Dimensions summary
You pay by the host hour for running this model, billed only while an instance is active. Pricing splits across two variables. First, the instance size: the ml.g5.12xlarge and the ml.g5.24xlarge offer different GPU capacity. Second, the inference mode: batch mode processes grouped requests, while real-time mode serves live requests. This gives you four combinations, each priced separately. You choose the instance and mode that fit your workload, and your cost scales with the hours you run.
Top-of-mind questions for buyers
Each option maps to a specific instance size with different GPU capacity. You pay per host hour while that instance runs. The ml.g5.24xlarge carries more GPU resources than the ml.g5.12xlarge. Choose the size that matches your throughput needs, since your hourly rate follows the instance you select.
Charges apply per host hour only while an instance runs. When you stop or terminate the instance, software billing stops. Underlying AWS resource fees, such as storage, may still apply based on your AWS account. The software meter tracks running time only.
Both meter per host hour on the same instance types. Batch mode processes grouped requests together, suited to bulk workloads run periodically. Real-time mode serves live requests as they arrive, suited to interactive uses like chatbots. You pick one mode per instance, and each combination bills separately.
docs.nvidia.com
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No refunds. Please contact NVIDIA at https://www.nvidia.com/en-us/data-center/lp/aws-marketplace-offer/ for further assistance.
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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:
Version release notes
Release notes are available here: https://docs.nvidia.com/nim/large-language-models/latest/release-notes.html#release-1-2-3
Additional details
Inputs
- Summary
The model accepts JSON requests with parameters on /invocations and /ping APIs that can be used to control the generated text. See examples and fields descriptions below.
- Input MIME type
- application/json
{
"model": "meta/llama-3.1-8b-instruct",
"messages": "[
{"role": "user", "content": "Hello! How are you?"},
{"role": "assistant", "content": "Hi! I am quite well, how can I help you today?"},
{"role": "user", "content": "What is the capital of France? Give one word answer."}
]",
"max_tokens": 4,
"stream":false
}
https://github.com/NVIDIA/nim-deploy/tree/main/cloud-service-providers/aws/sagemaker
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
model | Name of the model: meta/llama-3.1-8b-instruct
| Type: FreeText | Yes |
messages.role | Role of the entity in conversation | Type: Categorical
Allowed values: system, user, assistant | Yes |
max_tokens | Number of tokens that can be generated in the model's response | Default value: 1024
Type: Integer
Minimum: 0
Maximum: 2048 | No |
Resources
Support
Vendor support
Free support via NVIDIA NIM Developer Forum: https://forums.developer.nvidia.com/c/ai-data-science/nvidia-nim/
Global enterprise support is included with an NVIDIA AI Enterprise subscription: https://www.nvidia.com/en-us/data-center/products/ai-enterprise-suite/support/
For additional support information please contact NVIDIA: https://www.nvidia.com/en-us/data-center/lp/aws-marketplace-offer
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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