AWS Bedrock Agents Pricing: Token Costs & Break-Even Guide
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AI Costs & Pricing

AWS Bedrock Agents Pricing, Cost and Break-Even Value

By Paige Gilmore, Founder, NetLift· Published August 7, 2026· Updated August 7, 2026
Prices checked August 2, 2026 against official vendor pages

AWS Bedrock Agents pricing is driven by token consumption across various models, ranging from $0.10 to $30 per million tokens, alongside a $1.95 monthly fee for custom model storage.

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AWS Bedrock Agents costs scale based on the intelligence level required for the task. Low-latency, high-volume agents using Ministral 3B 3.0 start at $0.10 per million tokens for both input and output. In contrast, complex reasoning agents using Anthropic Claude Opus cost $6 per million input tokens and $30 per million output tokens on-demand.

Organizations using custom models face a monthly storage fee of $1.95 for Meta Llama 2 Pretrained (13B). Financial predictability depends on selecting the appropriate model and utilizing batch processing where possible, such as Claude 3.5 Sonnet, which offers reduced rates compared to public extended access.

Current official pricing

Plan Price Billing Notes
Meta Llama 2 Pretrained (13B) — Custom Model Storage $1.95 per month

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Usage-based prices

Model / rate Price Unit
Anthropic Claude 3.5 Sonnet — Batch Input tokens $3 per 1M input tokens
Anthropic Claude 3.5 Sonnet — Public Extended Access Input tokens $6 per 1M input tokens
Anthropic Claude 3.5 Sonnet — Batch Output tokens $15 per 1M output tokens
Anthropic Claude 3.5 Sonnet — Public Extended Access Output tokens $30 per 1M output tokens
Anthropic Claude Opus — On-Demand Input tokens $6 per 1M input tokens
Anthropic Claude Opus — On-Demand Output tokens $30 per 1M output tokens
Anthropic Claude Sonnet 5 — Promotional Input tokens $2 per 1M input tokens
Anthropic Claude Sonnet 5 — Promotional Output tokens $10 per 1M output tokens
DeepSeek v3.1 — Sydney Flex Input tokens $0.3 per 1M input tokens
DeepSeek v3.1 — Sydney Standard Input tokens $0.6 per 1M input tokens
DeepSeek v3.1 — Sydney Priority Input tokens $1.05 per 1M input tokens
DeepSeek v3.2 — Standard On-Demand Input tokens (US) $0.62 per 1M input tokens
DeepSeek v3.2 — Standard On-Demand Output tokens (US) $1.85 per 1M output tokens
Google Gemma 4 31B — Standard On-Demand Input tokens (US) $0.14 per 1M input tokens
Google Gemma 4 31B — Standard On-Demand Output tokens (US) $0.4 per 1M output tokens
Meta Llama 2 Chat (13B) — Standard On-Demand Input tokens (US) $0.75 per 1M input tokens
Meta Llama 2 Chat (13B) — Standard On-Demand Output tokens (US) $1 per 1M output tokens
MiniMax M2 — Standard On-Demand Input tokens (US) $0.3 per 1M input tokens
MiniMax M2 — Standard On-Demand Output tokens (US) $1.20 per 1M output tokens
Ministral 3B 3.0 — Standard On-Demand Input tokens (US) $0.1 per 1M input tokens
Ministral 3B 3.0 — Standard On-Demand Output tokens (US) $0.1 per 1M output tokens
Mistral Large 3 — Standard On-Demand Input tokens (US) $0.5 per 1M input tokens
Mistral Large 3 — Standard On-Demand Output tokens (US) $1.50 per 1M output tokens

Which models offer the lowest operational overhead?

For high-frequency tasks where speed is more critical than deep reasoning, Ministral 3B 3.0 is the most cost-effective at $0.10 per million tokens. Google Gemma 4 31B follows closely at $0.14 for inputs and $0.40 for outputs. These models allow for wide deployment of agents without the aggressive cost scaling seen in larger frontier models.

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How do reasoning requirements impact the budget?

Agents designed for debugging or complex code generation typically require higher-parameter models. Mistral Large 3 offers a mid-tier price point at $0.50 per million input tokens and $1.50 per million output tokens. At the highest end, Anthropic Claude Opus and Claude 3.5 Sonnet Public Extended Access both reach $30 per million output tokens, requiring a much higher threshold for business value to justify the spend.

To determine if an agent provides a positive return, you must compare the total token spend against the cost of the manual labor it replaces. NetLift allows organizations to move beyond simple cost tracking to measure whether high-priced models like Claude Opus deliver enough time savings to outperform cheaper alternatives. By quantifying the net return of AI adoption, leaders can justify the premium for advanced reasoning based on objective evidence of efficiency gains.

Sources

All pricing on this page comes from official vendor pages:

Frequently Asked Questions

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About the author

Paige Gilmore · Founder, NetLift

Paige Gilmore is the founder of NetLift, the AI Value Management platform that helps organisations measure the cost, savings and return of AI adoption.

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