Last refreshed 2026-07-09. Next refresh: weekly.
Why use Llama 3.2 90B Vision Instruct on AWS Bedrock?
AWS Bedrock offers Llama 3.2 90B Vision Instruct with pay-as-you-go pricing at $1.35/1M 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 3.2 90B Vision Instruct across 6 providers to find the best fit for your use caseInput / 1M
$1.35
Output / 1M
$1.80
Cache
Not sourced
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install boto3Auth
export AWS_ACCESS_KEY_ID=...Call
import boto3
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
modelId="llama-3.2-90b-vision-instruct",Model ID
llama-3.2-90b-vision-instructRequest 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="llama-3.2-90b-vision-instruct",
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 3.2 90B Vision Instruct Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Fireworks AI | $0.90 | $0.90 |
| NVIDIA NIM | — | — |
| Bitdeer AI | $0.15 | $0.45 |
| AWS Bedrock | $1.35 | $1.80 |
| Microsoft Foundry | $2.04 | $2.04 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $1.35 |
| Output tokens | $1.80 |
Capabilities
VisionMultimodal
About Llama 3.2 90B Vision Instruct
Instruction-tuned 90B Llama 3.2 Vision model for higher-capability image reasoning, visual question answering, visual grounding, and captioning. NVIDIA NIM lists text plus image input, text output, and a 128K context window for the Llama 3.2 Vision collection.
Get Started
Model Specs
Released2024-09-25
Parameters88.8B
Context128k
ArchitectureDecoder Only
Knowledge cutoff2024-03