Last refreshed 2026-10-17. Next refresh: weekly.
Why use Mistral Large 2 (2407) on AWS Bedrock?
AWS Bedrock offers Mistral Large 2 (2407) with pay-as-you-go pricing at $2.00/1M 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 Mistral Large 2 (2407) across 7 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="mistral.mistral-large-2407-v1:0",mistral.mistral-large-2407-v1:0Request 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="mistral.mistral-large-2407-v1:0",
messages=[{
"role": "user",
"content": [{"text": "Hello"}]
}]
)
print(response["output"]["message"]["content"][0]["text"])Gotchas
- Use provider model ID "mistral.mistral-large-2407-v1:0", not the LLMReference slug "mistral-large-2-2407".
- 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 Mistral Large 2 (2407) Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Microsoft Foundry | $3.00 | $9.00 |
| IBM watsonx | — | — |
| OpenRouter | $2.00 | $6.00 |
| AWS Bedrock | $2.00 | $6.00 |
| Chutes AI | $0.50 | $1.50 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $2.00 |
| Output tokens | $6.00 |
Capabilities
About Mistral Large 2 (2407)
Mistral Large 2 (version 24.07, API name mistral-large-2407) is a 123-billion-parameter dense model that Mistral released on July 24, 2024, designed for single-node inference in long-context applications. It has a 128K-token context window, up from 32K on the first Mistral Large, and supports dozens of languages, including French, German, Spanish, Italian, Portuguese, Arabic, Hindi, Russian, Chinese, Japanese and Korean, plus more than 80 coding languages such as Python, Java, C, C++, JavaScript and Bash.