Capacity, Limits, and Cost Optimization - Amazon Bedrock
Capacity OptionsLimits & QuotasCost Optimization

Capacity, Limits, and Cost Optimization

Amazon Bedrock offers flexible capacity options to match your workload requirements and budget. Understanding the differences between on-demand tiers (Flex, Priority, Standard), reserved tier, batch processing, and cross-region inference helps you optimize both performance and cost.

Capacity Options

Capacity Type Use Case Key Characteristics
On-Demand: Flex Sporadic, low-volume workloads

  • Lowest cost per token

  • Best-effort availability

  • May experience throttling

  • No SLA
On-Demand: Standard Regular production workloads

  • Balanced cost and performance

  • Moderate throughput guarantees

  • Standard SLA

  • Most common choice
On-Demand: Priority High-priority, latency-sensitive apps

  • Highest on-demand cost

  • Premium throughput allocation

  • Enhanced SLA

  • Reduced throttling risk
Reserved Tier Consistent, high-volume workloads

  • Reserved model units

  • Guaranteed capacity

  • 1 or 6 month commitments

  • Predictable performance
Batch Large-scale, non-time-sensitive processing

  • 50% cost savings vs on-demand

  • 24-hour processing window

  • Ideal for bulk inference
Cross-Region Inference High availability, traffic bursting

  • Automatic failover

  • Route to less-busy regions

  • Improved uptime

  • Uses on-demand pricing

Limits & Quotas

On-Demand Limits (by tier)

Tier RPM Range TPM Range Throttling Risk
Flex 10-100 5K-50K High
Standard 100-500 50K-150K Medium
Priority 500-1000+ 150K-300K+ Low

  • Burst capacity: Available across all tiers for short spikes

  • Soft limits: Increasable via service quota requests

  • Model-specific: Actual limits vary by foundation model

Reserved Tier Limits

  • Minimum commitment: 1 model unit

  • Maximum units: Account and region-specific

  • Input/output token limits: Based on purchased units

  • No RPM throttling within purchased capacity

Batch Processing Limits

  • Job size: Up to 10,000 records per batch

  • File size: Maximum 200 MB input file

  • Processing time: 24-hour completion window

  • Concurrent jobs: Region-specific quotas

Cross-Region Inference

  • Inherits on-demand tier limits per region

  • No additional quota overhead

  • Automatic routing (no manual limit management)

Cost Optimization

Decision Framework

Scenario Recommended Option Why
Development/testing Flex Lowest cost, acceptable for non-production
Standard production Standard Best cost-performance balance
Critical user-facing apps Priority Reliability and performance over cost
Steady high-volume load Reserved Tier 30-50% savings with commitment
Bulk data processing Batch 50% discount, non-urgent workloads
Mission-critical uptime Cross-Region Inference Availability > cost

Optimization Strategies

Choose the Right On-Demand Tier

  • Start with Standard for most workloads

  • Downgrade to Flex for dev/test environments

  • Upgrade to Priority only when throttling impacts users

  • Monitor CloudWatch throttle metrics to inform decisions

Transition to Reserved Tier

  • When consistent load exceeds 40% of on-demand costs

  • Calculate break-even: (Monthly on-demand cost) vs (Reserved commitment)

  • Use 1-month commitment initially

  • Reserved tier can work alongside any on-demand tier

Leverage Batch for

  • Training data generation

  • Content moderation backlogs

  • Report generation

  • Data enrichment pipelines

Combine Approaches

  • Reserved tier for baseline traffic

  • Standard on-demand for moderate bursts

  • Priority on-demand for critical peak periods

  • Batch for offline processing

  • Cross-region for failover only

Cost Monitoring

  • Compare tier costs: Flex < Standard < Priority

  • Track tokens per request (optimize prompts)

  • Use CloudWatch metrics for utilization and throttling

  • Set billing alarms for unexpected spikes

  • Review reserved tier utilization monthly

  • Evaluate tier upgrades only when throttling occurs