Foundation Model ยท Amazon BedrockTextMulti-Tier Pricing
Nova 2.0 Lite
Amazon Bedrock token pricing and cost optimization reference for Nova 2.0 Lite.Rates normalized to USD per 1 Million Tokens ($/1M) with prompt caching and batch API discounts across 26 AWS regions.
ProviderAmazon
ModalityText
Prompt CachingSave 75%
Batch APISave 50%
AWS Regions26 Global
Bedrock Model ID
amazon.nova-2-0-lite-v1:0Input / Prompt
$0.15/ 1M tokens
$0.0001 per 1K tokens
Output / Completion
$1.25/ 1M tokens
$0.0013 per 1K tokens
Prompt Cache Read
$0.04/ 1M tokens
Save 75% vs prompt
Batch Inference
$0.07/ 1M in
Save 50% via Batch API
Price Ratio
1 : 8.3
Prompt to completion factor
Nova 2.0 Lite Spend Estimator
Model inference spend by prompt volume, cache hit rate, and batch processing.
M tokens
M tokens
30%
Estimated Monthly Spend
$0.00
Fresh Prompts:$0.00
Cached Prompts:$0.00
Completions:$0.00
Active: Input: $0.15/1M ยท Output: $1.25/1M
Key Cost Levers & Architecture
Practical mechanisms to reduce inference costs with Nova 2.0 Lite on AWSPrompt CachingSave ~75%
Caches repetitive system instructions, schemas, and document prefixes in memory with a 5-minute TTL.
- Read Rate: $0.04 / 1M tokens
- Write Rate: $0.19 / 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: $0.07 / 1M tokens
- Batch Output: $0.63 / 1M tokens
- Ideal for: Offline classification, synthetic data generation, benchmark evals
Cross-Region & Tiers26 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 26 available AWS cloud regionsBaseline: $0.15/1M inGovCloud: $0.73/1M in26 Global Regions
| AWS Region | Prompt Input | Completion Output | Cache Read | Batch Input | Pricing Tier |
|---|---|---|---|---|---|
| $0.15/1M | $1.25/1M | $0.04/1M | โ/1M | Baseline | |
| $0.53/1M | $4.81/1M | $0.13/1M | โ/1M | +250% vs Baseline | |
| $0.68/1M | $1.80/1M | $0.05/1M | โ/1M | +355% vs Baseline | |
| $0.59/1M | $1.44/1M | $0.15/1M | โ/1M | +297% vs Baseline | |
| $0.18/1M | $1.66/1M | $0.16/1M | โ/1M | +20% vs Baseline | |
| $0.56/1M | $1.31/1M | $0.08/1M | โ/1M | +273% vs Baseline | |
| $0.72/1M | $1.70/1M | $0.18/1M | โ/1M | +378% vs Baseline | |
| $0.17/1M | $2.71/1M | $0.08/1M | โ/1M | +10% vs Baseline | |
| $0.61/1M | $1.48/1M | $0.04/1M | โ/1M | +308% vs Baseline | |
| $0.32/1M | $4.60/1M | $0.08/1M | โ/1M | +113% vs Baseline | |
| $0.36/1M | $1.48/1M | $0.09/1M | โ/1M | +140% vs Baseline | |
| $0.20/1M | $1.70/1M | $0.05/1M | โ/1M | +37% vs Baseline | |
| $0.16/1M | $4.60/1M | $0.08/1M | โ/1M | +7% vs Baseline | |
| $0.36/1M | $5.27/1M | $0.09/1M | โ/1M | +140% vs Baseline | |
| $0.41/1M | $1.70/1M | $0.18/1M | โ/1M | +173% vs Baseline | |
| $0.18/1M | $1.33/1M | $0.04/1M | โ/1M | +17% vs Baseline | |
| $0.19/1M | $1.95/1M | $0.16/1M | โ/1M | +25% vs Baseline | |
| $0.73/1M | $1.76/1M | $0.10/1M | โ/1M | +390% vs Baseline | |
| $0.24/1M | $7.72/1M | $0.08/1M | โ/1M | +60% vs Baseline | |
| $0.22/1M | $6.46/1M | $0.12/1M | โ/1M | +47% vs Baseline | |
| $0.18/1M | $1.50/1M | $0.14/1M | โ/1M | +21% vs Baseline | |
| $0.18/1M | $4.81/1M | $0.04/1M | โ/1M | +21% vs Baseline | |
| $0.67/1M | $3.13/1M | $0.17/1M | โ/1M | +343% vs Baseline | |
| $0.30/1M | $4.38/1M | $0.04/1M | โ/1M | +100% vs Baseline | |
| $0.58/1M | $2.50/1M | $0.04/1M | โ/1M | +285% vs Baseline | |
| $0.21/1M | $3.35/1M | $0.11/1M | โ/1M | +43% vs Baseline |
No AWS regions found matching your filter.
Developer Quickstart
Invoke Nova 2.0 Lite via Amazon Bedrock Converse APIPython (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.nova-2-0-lite-v1:0",
messages=[
{
"role": "user",
"content": [{"text": "Summarize key features and cost levers of Nova 2.0 Lite."}]
}
],
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")Compare Nova 2.0 Lite with Alternatives
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