Last refreshed 2026-07-09. Next refresh: weekly.
Why use Llama 2 70B Chat on AWS Bedrock?
AWS Bedrock offers Llama 2 70B Chat with pay-as-you-go pricing at $1.95/1M input tokens. AWS Bedrock is Amazon's fully managed foundation-model service, providing unified API access to top models from Anthropic, Meta, Mistral, and other leading AI labs with built-in tools for RAG, fine-tuning, and AI agent development.
Compare Llama 2 70B Chat across 14 providers to find the best fit for your use caseSetup recipe
Python + curlpip install boto3export AWS_ACCESS_KEY_ID=...import boto3
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
modelId="llama2-70b-chat",llama2-70b-chatRequest example
import boto3
# Reads AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION from env
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
modelId="llama2-70b-chat",
messages=[{
"role": "user",
"content": [{"text": "Hello"}]
}]
)
print(response["output"]["message"]["content"][0]["text"])Gotchas
- Use Amazon Bedrock model IDs, e.g. "anthropic.claude-3-opus-20240229-v1:0" for on-demand, or cross-region inference profile IDs like "us.anthropic.claude-opus-4-7-20251101-v1:0". These differ from the public model slug.
- The endpoint template includes a region segment; set the same region in your SDK/client configuration.
- The examples expect AWS_ACCESS_KEY_ID; rename it only if your application config maps the new variable.
Compare Llama 2 70B Chat Across Providers
| Provider | Input (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 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $1.95 |
| Output tokens | $2.56 |
Capabilities
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 .