LLM Reference
Microsoft Foundry

Llama 2 70B Chat on Microsoft Foundry

Llama 2 · AI at Meta

ServerlessProvisionedOpen Weights

Last refreshed 2026-07-09. Next refresh: weekly.

Why use Llama 2 70B Chat on Microsoft Foundry?

Microsoft Foundry offers Llama 2 70B Chat with pay-as-you-go pricing at $1.54/1M input tokens. Microsoft Foundry is a unified Azure platform-as-a-service offering for enterprise AI operations, model builders, and application development.

Compare Llama 2 70B Chat across 14 providers to find the best fit for your use case
Input / 1M
$1.54
Output / 1M
$1.77
Cache
Not sourced
Batch
Not sourced

Setup recipe

Docs fallback
Install
Use the provider REST API or SDK
Auth
Create a provider API key
Call
model: llama2-70b-chat
Model ID
llama2-70b-chat

Request example

Curated snippets for this provider are not sourced yet. Use Microsoft Foundry documentation with model ID llama2-70b-chat.

Gotchas

No curated gotchas have been sourced for this exact provider/model route yet.

Compare Llama 2 70B Chat Across Providers

ProviderInput (per 1M)Output (per 1M)
Databricks Foundation Model Serving$0.50$1.50
Microsoft Foundry$1.54$1.77
GCP Vertex AI$0.80$2.40
Alibaba Cloud PAI-EAS
AWS Bedrock$1.95$2.56
View all 14 providers →

Pricing

TypePrice (per 1M)
Input tokens$1.54
Output tokens$1.77

Capabilities

Structured Outputs

About Llama 2 70B Chat

Llama 2 70B Chat is a large-scale language model with 70 billion parameters, designed for conversational AI applications. Released on July 18, 2023, it's part of Meta's Llama 2 family, featuring advanced transformer architecture optimized through supervised fine-tuning and reinforcement learning with human feedback. The model excels in generating human-like responses, outperforming many open-source alternatives and rivaling closed-source models like ChatGPT. Trained on 2 trillion tokens from diverse public sources, it's suitable for commercial and research applications in English, particularly for assistant-like functionalities. The model is available on Hugging Face for further exploration and implementation .

Get Started