AWS Bedrock On-Demand vs Provisioned Throughput: Unit Economics and Model Selection Decision Tree

Amazon Bedrock Model Menu Overview Amazon Bedrock offers businesses access to a wide selection of over 100 foundation models from leading providers, including Amazon's Nova series, Anthropic's Claude family, Meta's Llama models, and others like DeepSeek and Moonshot AI. As of May 11, 2026 (according to AWS Bedrock documentation at docs.aws.amazon.com/bedrock), key model IDs include: - Amazon Nova : (high-capability reasoning), (balanced), (speed-focused), along with multimodal variants like and . - Anthropic Claude : (enterprise-grade reasoning), (complex tasks), and previews like . - Meta Llama : (open-weights powerhouse), (efficient scaling). This model selection supports enterprise use cases such as retrieval-augmented generation (RAG) for knowledge-intensive queries and agents for multi-step operations. Bedrock's APIs, including the Converse API and Messages API, facilitate seamless

integration, featuring latency-optimized inference for models like Claude 3.5 Haiku and Llama 3.1. Choosing the appropriate model and throughput mode is crucial for managing the unit economics of production workloads. On-Demand vs. Provisioned Throughput: Key Differences AWS Bedrock provides two primary inference modes: on-demand and provisioned throughput . On-Demand Throughput - Pay-per-token usage : You are billed solely for the input and output tokens processed (e.g., cost per million tokens in/out). - Flexible scaling : Ideal for variable or experimental workloads as there are no long-term commitments. - Higher per-unit costs : Reflects the use of shared infrastructure. - Limits : Subject to per-minute token throughput (TPM) quotas, with auto-scaling based on demand. Provisioned Throughput - Committed capacity : You purchase Provisioned Throughput Units (PTUs) to guarantee a specifi

c TPM and requests per minute (RPM). - Billing : Charged at an hourly rate per PTU, in addition to per-token fees (which are often discounted compared to on-demand rates). - Commitment duration : Available for 1 or 6-month terms, providing reservations for predictable, high-volume needs. - Benefits : Offers lower effective unit costs (potentially up to 50% savings at scale, according to AWS documentation) and Service Level Agreements (SLAs) for latency and availability. The key trade-off is that on-demand throughput is best suited for spiky or development workloads, while provisioned throughput excels for steady enterprise RAG and agent processing that handles millions of tokens daily. Always refer to the current details at aws.amazon.com/bedrock/pricing/ as of May 11, 2026. Unit Economics: How Throughput Modes Impact Costs Unit economics are determined by the cost per 1,000 inferences o

r cost per effective output token , taking into account tokens, latency, and volume. Core Formulas For both modes: Total Cost = (Input Tokens × Input Rate) + (Output Tokens × Output Rate) + Fixed Fees (provisioned only) - On-Demand Unit Cost = [Input Rate ($/MTok) × Average Input Tokens/MTok] + [Output Rate ($/MTok) × Average Output Tokens/MTok] - For example, for the model ID , rates are listed per AWS pricing (e.g., input $3/MTok, output $15/MTok based on prior snapshots; always verify current rates). - Provisioned Unit Cost = On-Demand Equivalent × Discount Factor + (PTU Hourly Rate × Hours) / Total Tokens Processed - PTUs provide a fixed TPM (e.g., 1 PTU might equal 10,000 TPM for certain models). - Effective savings increase with utilization; achieving 90%+ utilization typically results in the lowest cost per token. Factor On-Demand Provisioned -------------------- -----------------

--------- --------------------------------- Per-Token Rate Base Discounted (model-specific) Volume Threshold N/A 1 Million tokens/day recommended Predictability Variable Guaranteed Shifting to provisioned throughput can significantly alter economics. At 100 million tokens per month, the effective cost per token can drop by 30-70% (based on methodology from the AWS calculator; test via the Bedrock console). Always reference the exact rates for your specific model ID on the pricing page. Bedrock Models Spotlight: Nova, Anthropic Claude, Meta Llama Amazon Nova Series Optimized for AWS-native operations: - : Frontier reasoning capabilities for complex RAG and agents; higher output rates reflect its advanced performance. - : Designed for low-latency, high-throughput agents; offers favorable on-demand rates for high-volume use cases. - Provisioned Throughput : Provides strong discounts for mul

timodal capabilities like Reel and Sonic, particularly beneficial for video RAG applications. Anthropic Claude A preferred choice for enterprise applications requiring safety and tool-calling: - : Offers a balanced cost-performance ratio; provisioned PTUs are particularly effective for 24/7 agents.