How much does it cost to deploy Llama2 on Azure?

Question

Please tell me the price when deploying Llama2(Meta-LLM) on Azure.

[Condition]

・To make it cheap, deployment, configuration, and operation will be done by me.

・Since for what I will use LLama2 hasn't been decided yet(probably for summarizing or comparing documents), so that I would like to know the cost for only deploying Llama2 on Azure.

[Questions]

・What resources will be required to deploy and use Llama2 on Azure. Please tell me the minimum requirements per each model with some scenarios.

・Cost for the above.

・Any additional information or tips regarding deploying or using Llama2 on Azure will be appreciated.

Thank you.

Answer 1

Natsuki Greetings & Welcome to Microsoft Q&A forum!

Please tell me the price when deploying Llama2(Meta-LLM) on Azure.

Deploying Llama2 (Meta-LLM) on Azure will require virtual machines (VMs) to run the software and store the data.

The cost of deploying Llama2 on Azure will depend on several factors, such as the number and size of VMs, the storage capacity, and the data transfer costs.

To give you an idea of the cost, let's consider a scenario where you deploy Llama2 on a single VM with 4 cores, 8 GB of RAM, and 128 GB of storage. The estimated cost for this VM is around $0.16 per hour or $115 per month. However, this is just an estimate, and the actual cost may vary depending on the region, the VM size, and the usage.

In addition to the VM cost, you will also need to consider the storage cost for storing the data and any additional costs for data transfer. The storage cost will depend on the amount of data you plan to store and the type of storage you choose (e.g., standard or premium). The data transfer cost will depend on the amount of data you transfer in and out of Azure.

What resources will be required to deploy and use Llama2 on Azure. Please tell me the minimum requirements per each model with some scenarios.

Llama2 has several models available for different natural language processing tasks such as text summarization and comparison. The resource requirements for deploying and using Llama2 on Azure will depend on the specific model you plan to use and the size of the data you plan to process.

A NOTE about compute requirements when using Llama 2 models: Finetuning, evaluating and deploying Llama 2 models requires GPU compute of V100 / A100 SKUs. You can find the exact SKUs supported for each model in the information tooltip next to the compute selection field in the finetune/ evaluate / deploy wizards. You can view and request AzureML compute quota here.

• Llama2 Comparison Model: This model is designed for text comparison tasks and requires a VM with at least 4 cores and 8 GB of RAM to run efficiently. However, the resource requirements may vary depending on the size of the input data and the desired output. For example, if you plan to compare large documents or process multiple documents in parallel, you may need a VM with more cores and RAM to handle the workload.
• Llama2 Multi-Document Summarization Model: This model is designed for summarizing multiple documents and requires a VM with at least 8 cores and 16 GB of RAM to run efficiently. However, the resource requirements may vary depending on the size of the input data and the desired output. For example, if you plan to summarize a large number of documents or process multiple document sets in parallel, you may need a VM with more cores and RAM to handle the workload. Please note that these are general guidelines, and the resource requirements may vary depending on the specific use case and the size of the data. It is recommended to test the performance of Llama2 on a smaller VM size first and then scale up as needed.

Cost for the above.

The estimated cost for deploying Llama2 on a single VM with 4 cores, 8 GB of RAM, and 128 GB of storage is around $0.16 per hour or $115 per month. However, this is just an estimate, and the actual cost may vary depending on the region, the VM size, and the usage.

To reduce the cost, you can choose a smaller VM size or use Azure Spot VMs, which offer up to 90% cost savings compared to regular VMs. You can also use Azure Storage to store your data, which offers low-cost storage options.

Any additional information or tips regarding deploying or using Llama2 on Azure will be appreciated.

Please see Introducing Llama 2 on Azure and Deploy large language models responsibly with Azure AI for more details.

Do let me know if that helps or have any other queries.

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