# 💸 What Does One Amazon Bedrock Prompt Cost? Find Out From the CLI (Hands-on)

> Source: <https://dev.to/confident_prep/what-does-one-amazon-bedrock-prompt-cost-find-out-from-the-cli-hands-on-2m9p>
> Published: 2026-10-11 04:32:34+00:00

"Your team wants to add an Amazon Bedrock chatbot. How would you work out what one prompt costs?"

It shows up in AIF-C01 prep and in real interviews. The strong answer: **Bedrock charges per token, and every response tells you how many tokens it used.** Let's prove that from the AWS CLI in 5 minutes. 👇

👉 Flow: **Send one prompt → Read `usage` → Multiply by the price → Compare two prompts**

✅ AWS CLI v2, signed in (`aws sts get-caller-identity` works)

✅ Region `us-east-1`

✅ Model access for **Amazon Nova Micro** (Bedrock console → *Model access*)

```
aws bedrock-runtime converse \
  --region us-east-1 \
  --model-id us.amazon.nova-micro-v1:0 \
  --messages '[{"role":"user","content":[{"text":"Explain overfitting in one sentence."}]}]' \
  --query '{answer: output.message.content[0].text, usage: usage}'
```

✅ Expected (your numbers will differ):

```
{
  "answer": "Overfitting is when a model learns the training data so closely ...",
  "usage": { "inputTokens": 8, "outputTokens": 24, "totalTokens": 32 }
}
```

👀 That `usage` block is your bill, in tokens.

Open [Amazon Bedrock pricing](https://aws.amazon.com/bedrock/pricing/), find **Nova Micro**, and copy its price per **1,000 input tokens** and per **1,000 output tokens**.

```
IN=8; OUT=24                      # from usage
P_IN=<price per 1K input tokens>  # from the pricing page
P_OUT=<price per 1K output tokens>
awk -v i=$IN -v o=$OUT -v pi=$P_IN -v po=$P_OUT \
  'BEGIN { printf "USD %.8f per prompt\n", i/1000*pi + o/1000*po }'
```

💡 Multiply by prompts per day to get a daily cost. That's the number your manager wants.

Ask for a **long** answer instead:

```
--messages '[{"role":"user","content":[{"text":"Explain overfitting in 500 words."}]}]'
```

📈 `outputTokens` jumps, and output tokens cost more than input tokens. Then add `--inference-config '{"maxTokens":50}'` and watch the cost come back down.

✅ "Bedrock on-demand pricing is per input and output token"

✅ "Every Converse response returns `inputTokens` and `outputTokens`"

✅ "Output tokens usually cost more, so I cap them with `maxTokens`"

✅ "Cost per prompt × prompts per day = the daily bill"

This is the hands-on cut of **Chapter 5** of our free *AWS AI Practitioner (AIF-C01)* course: the full chapter explains tokens, why they drive cost, and how the exam asks about them.