Foundation Model · Amazon BedrockTextMulti-Tier Pricing
Gemma 4-26B-A4B
Amazon Bedrock token pricing and cost optimization reference for Gemma 4-26B-A4B.Rates normalized to USD per 1 Million Tokens ($/1M) with prompt caching and batch API discounts across 5 AWS regions.
ProviderGoogle
ModalityText
Prompt CachingSave 75%
Batch APISupported
AWS Regions5 Global
Bedrock Model ID
google.gemma-4-26b-a4b-v1:0Input / Prompt
$0.07/ 1M tokens
$0.0001 per 1K tokens
Output / Completion
$0.20/ 1M tokens
$0.0002 per 1K tokens
Prompt Cache Read
$0.02/ 1M tokens
Save 75% vs prompt
Batch Inference
$0.07/ 1M in
Save 0% via Batch API
Price Ratio
1 : 3.1
Prompt to completion factor
Gemma 4-26B-A4B 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: $0.07/1M · Output: $0.20/1M
Key Cost Levers & Architecture
Practical mechanisms to reduce inference costs with Gemma 4-26B-A4B on AWSPrompt CachingSave ~75%
Caches repetitive system instructions, schemas, and document prefixes in memory with a 5-minute TTL.
- Read Rate: $0.02 / 1M tokens
- Write Rate: $0.08 / 1M tokens
- Ideal for: Multi-turn conversations, RAG document queries, structured schemas
Batch InferenceSave 0%
Asynchronous bulk processing submitted via Amazon S3 with a standard 24-hour turnaround SLA.
- Batch Input: $0.07 / 1M tokens
- Batch Output: $0.20 / 1M tokens
- Ideal for: Offline classification, synthetic data generation, benchmark evals
Cross-Region & Tiers5 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 5 available AWS cloud regionsBaseline: $0.13/1M inGovCloud: $0.16/1M in5 Global Regions
| AWS Region | Prompt Input | Completion Output | Cache Read | Batch Input | Pricing Tier |
|---|---|---|---|---|---|
| $0.13/1M | $0.40/1M | —/1M | $0.07/1M | Baseline | |
| $0.13/1M | $0.40/1M | —/1M | $0.07/1M | Baseline | |
| $0.16/1M | $0.48/1M | —/1M | $0.08/1M | +20% vs Baseline | |
| $0.16/1M | $0.48/1M | —/1M | $0.08/1M | GovCloud (+20%) | |
| $0.13/1M | $0.40/1M | —/1M | $0.07/1M | Baseline |
No AWS regions found matching your filter.
Developer Quickstart
Invoke Gemma 4-26B-A4B via Amazon Bedrock Converse APIPython (boto3) · Amazon Bedrock Runtime
import boto3
# Amazon Bedrock Converse API invocation
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
modelId="google.gemma-4-26b-a4b-v1:0",
messages=[
{
"role": "user",
"content": [{"text": "Summarize key features and cost levers of Gemma 4-26B-A4B."}]
}
],
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 Gemma 4-26B-A4B with Alternatives
Open Multi-Model Estimator →Gemma 4-26B-A4B vsJamba 1.5 LargeAI21 Labs
Input Rate:$2.00/1M
Output Rate:$8.00/1M
Gemma 4-26B-A4B vsJamba 1.5 MiniAI21 Labs
Input Rate:$0.20/1M
Output Rate:$0.40/1M
Gemma 4-26B-A4B vsQwen3 235B A22B 2507Alibaba (Qwen)
Input Rate:$0.11/1M
Output Rate:$0.44/1M