LLM Reference
AWS Bedrock

Jamba 1.5 Mini on AWS Bedrock

Jamba 1.5 · AI21 Labs

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Last refreshed 2026-06-15. Next refresh: weekly.

Why use Jamba 1.5 Mini on AWS Bedrock?

AWS Bedrock offers Jamba 1.5 Mini with pay-as-you-go pricing at $0.20/1M 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 Jamba 1.5 Mini across 2 providers to find the best fit for your use case
Input / 1M
$0.20
Output / 1M
$0.40
Cache
Not sourced
Batch
Not sourced

Setup recipe

Python + curl
Install
pip install boto3
Auth
export AWS_ACCESS_KEY_ID=...
Call
import boto3
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
    modelId="jamba-1.5-mini",
Model ID
jamba-1.5-mini

Request 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="jamba-1.5-mini",
    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 Jamba 1.5 Mini Across Providers

ProviderInput (per 1M)Output (per 1M)
NVIDIA NIM
AWS Bedrock$0.20$0.40

Pricing

TypePrice (per 1M)
Input tokens$0.20
Output tokens$0.40

Capabilities

JSON / Tool useStructured Outputs

About Jamba 1.5 Mini

Jamba 1.5 Mini is AI21 Labs' Jamba 1.5 model. It offers a 256K-token context window.

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Model Specs

Released2024-08-22
Parameters52B (12B active)
Context256k
ArchitectureDecoder Only
Knowledge cutoff2024-03

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