Input / Prompt
โ€”/ 1M tokens
Standard on-demand
Output / Completion
โ€”/ 1M tokens
Standard on-demand
Prompt Cache Read
โ€”/ 1M tokens
Optimized context reuse
Batch Inference
โ€”/ 1M in
Save 50% via Batch API
Price Ratio
โ€”
Prompt to completion factor
Regional Reach
29AWS Regions

Guardrail Spend Estimator

Model inference spend by prompt volume, cache hit rate, and batch processing.

Workload Presets:
M tokens
M tokens
30%
Estimated Monthly Spend
$0.00
Fresh Prompts:$0.00
Cached Prompts:$0.00
Completions:$0.00
Active: Input: โ€”/1M ยท Output: โ€”/1M

Key Cost Levers & Architecture

Practical mechanisms to reduce inference costs with Guardrail on AWS
Prompt CachingSave ~0%

Caches repetitive system instructions, schemas, and document prefixes in memory with a 5-minute TTL.

  • Read Rate: โ€” / 1M tokens
  • Write Rate: โ€” / 1M tokens
  • Ideal for: Multi-turn conversations, RAG document queries, structured schemas
Batch InferenceSave 50%

Asynchronous bulk processing submitted via Amazon S3 with a standard 24-hour turnaround SLA.

  • Batch Input: โ€” / 1M tokens
  • Batch Output: โ€” / 1M tokens
  • Ideal for: Offline classification, synthetic data generation, benchmark evals
Cross-Region & Tiers29 Regions

AWS Bedrock supports standard on-demand inference, priority reserved throughput, and cross-region routing.

  • Standard: Lowest latency, pay-per-token with zero commitments
  • Cross-Region Routing: Automatically burst traffic to available regional capacity
  • GovCloud: Dedicated isolated compliance partitions with +20% uplift

Regional Pricing Matrix

Live rates across all 29 available AWS cloud regions
Baseline: โ€”/1M in29 Global Regions
Showing 6 benchmark regions
AWS RegionPrice TypeRateUnit
other$0.0001TextUnit
other$0.0001TextUnit
other$0.0000TextUnit
Asia Pacific (Tokyo)ap-northeast-1
image_generation$0.0008Images Processed
Asia Pacific (Tokyo)ap-northeast-1
other$0.0001TextUnit
Asia Pacific (Tokyo)ap-northeast-1
other$0.0001TextUnit
Asia Pacific (Tokyo)ap-northeast-1
other$0.0000TextUnit
Asia Pacific (Seoul)ap-northeast-2
other$0.0001TextUnit
Asia Pacific (Seoul)ap-northeast-2
other$0.0001TextUnit
Asia Pacific (Seoul)ap-northeast-2
other$0.0000TextUnit
Asia Pacific (Osaka)ap-northeast-3
other$0.0000TextUnit
Asia Pacific (Osaka)ap-northeast-3
other$0.0001TextUnit
Asia Pacific (Osaka)ap-northeast-3
other$0.0001TextUnit
other$0.0001TextUnit
other$0.0001TextUnit
other$0.0000TextUnit
other$0.0001TextUnit
other$0.0000TextUnit
other$0.0001TextUnit
other$0.0000TextUnit
other$0.0001TextUnit
other$0.0001TextUnit
Asia Pacific (Sydney)ap-southeast-2
other$0.0001TextUnit
Asia Pacific (Sydney)ap-southeast-2
other$0.0001TextUnit
Asia Pacific (Sydney)ap-southeast-2
other$0.0000TextUnit
other$0.0000TextUnit
other$0.0001TextUnit
other$0.0001TextUnit
other$0.0001TextUnit
other$0.0001TextUnit
other$0.0000TextUnit
other$0.0000TextUnit
other$0.0001TextUnit
other$0.0001TextUnit
Canada (Central)ca-central-1
other$0.0000TextUnit
Canada (Central)ca-central-1
other$0.0001TextUnit
Canada (Central)ca-central-1
other$0.0001TextUnit
EU (Frankfurt)eu-central-1
image_generation$0.0008Images Processed
EU (Frankfurt)eu-central-1
other$0.0000TextUnit
EU (Frankfurt)eu-central-1
other$0.0001TextUnit
EU (Frankfurt)eu-central-1
other$0.0002TextUnit
EU (Frankfurt)eu-central-1
other$0.0001TextUnit
Europe (Zurich)eu-central-2
other$0.0001TextUnit
Europe (Zurich)eu-central-2
other$0.0000TextUnit
Europe (Zurich)eu-central-2
other$0.0001TextUnit
EU (Stockholm)eu-north-1
other$0.0001TextUnit
EU (Stockholm)eu-north-1
other$0.0000TextUnit
EU (Stockholm)eu-north-1
other$0.0001TextUnit
EU (Milan)eu-south-1
other$0.0001TextUnit
EU (Milan)eu-south-1
other$0.0001TextUnit
EU (Milan)eu-south-1
other$0.0000TextUnit
Europe (Spain)eu-south-2
other$0.0001TextUnit
Europe (Spain)eu-south-2
other$0.0000TextUnit
Europe (Spain)eu-south-2
other$0.0001TextUnit
EU (Ireland)eu-west-1
other$0.0001TextUnit
EU (Ireland)eu-west-1
other$0.0000TextUnit
EU (Ireland)eu-west-1
other$0.0001TextUnit
EU (Ireland)eu-west-1
other$0.0002TextUnit
EU (London)eu-west-2
other$0.0001TextUnit
EU (London)eu-west-2
other$0.0000TextUnit
EU (London)eu-west-2
other$0.0001TextUnit
EU (Paris)eu-west-3
other$0.0000TextUnit
EU (Paris)eu-west-3
other$0.0001TextUnit
EU (Paris)eu-west-3
other$0.0001TextUnit
EU (Paris)eu-west-3
other$0.0002TextUnit
Israel (Tel Aviv)il-central-1
other$0.0001TextUnit
Israel (Tel Aviv)il-central-1
other$0.0001TextUnit
Israel (Tel Aviv)il-central-1
other$0.0000TextUnit
Middle East (UAE)me-central-1
other$0.0001TextUnit
Middle East (UAE)me-central-1
other$0.0001TextUnit
Middle East (UAE)me-central-1
other$0.0000TextUnit
other$0.0001TextUnit
other$0.0000TextUnit
other$0.0001TextUnit
image_generation$0.0008Images Processed
other$0.0002TextUnit
other$0.0001TextUnit
other$0.0001TextUnit
other$0.0000TextUnit
other$0.0000TextUnit
other$0.0001TextUnit
other$0.0001TextUnit
other$0.0002TextUnit
other$0.0000TextUnit
other$0.0001TextUnit
other$0.0001TextUnit
other$0.0001TextUnit
other$0.0001TextUnit
other$0.0000TextUnit
other$0.0001TextUnit
other$0.0000TextUnit
other$0.0001TextUnit
image_generation$0.0008Images Processed
other$0.0002TextUnit
other$0.0001TextUnit
other$0.0000TextUnit
other$0.0001TextUnit

Developer Quickstart

Invoke Guardrail via Amazon Bedrock Converse API
Python (boto3) ยท Amazon Bedrock Runtime
import boto3

# Amazon Bedrock Converse API invocation
client = boto3.client("bedrock-runtime", region_name="us-east-1")

response = client.converse(
    modelId="amazon.guardrail-v1:0",
    messages=[
        {
            "role": "user",
            "content": [{"text": "Summarize key features and cost levers of Guardrail."}]
        }
    ],
    inferenceConfig={
        "maxTokens": 1024,
        "temperature": 0.7
    }
)

output_text = response["output"]["message"]["content"][0]["text"]
usage = response["usage"]
print(f"Response: {output_text}")
print(f"Usage: {usage['inputTokens']} in, {usage['outputTokens']} out")

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