Foundation Model ยท Amazon BedrockQwen FamilyLightweight TierTextMulti-Tier Pricing
Qwen3 Next 80B A3B
Amazon Bedrock token pricing and cost optimization reference for Qwen3 Next 80B A3B.Rates normalized to USD per 1 Million Tokens ($/1M) with prompt caching and batch API discounts across 13 AWS regions.
ProviderAlibaba (Qwen)
Maker HQHangzhou, Zhejiang, China
Class / TierLightweight
ModalityText
Prompt CachingSave 75%
Batch APISave 50%
AWS Regions13 Global
Bedrock Model ID
alibaba.qwen3-next-80b-a3b-v1:0Input / Prompt
$0.14/ 1M tokens
$0.0001 per 1K tokens
Output / Completion
$1.20/ 1M tokens
$0.0012 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 : 8.6
Prompt to completion factor
Alternatives to Qwen3 Next 80B A3B
| Option | Price vs Qwen3 Next 80B A3B | Why look at it |
|---|---|---|
| Qwen3 235B A22B 2507Compare → | input+57%+$0.08/1M output-27%-$0.32/1M Standard tier, per 1M tokens | Next step down in price from Alibaba (Qwen) (general tier) |
| Qwen3 Coder NextCompare → | input+257%+$0.36/1M outputsame price Standard tier, per 1M tokens | Next step up in price from Alibaba (Qwen) (reasoning tier) |
| Qwen3 Coder 480B A35BCompare → | input+221%+$0.31/1M output+50%+$0.60/1M Standard tier, per 1M tokens | Same Qwen line, different version (reasoning tier) |
| Qwen3 Coder 30B A3BCompare → | input+7%+$0.01/1M output-50%-$0.60/1M Standard tier, per 1M tokens | Also from Alibaba (Qwen) |
Qwen3 Next 80B A3B 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: $0.14/1M ยท Output: $1.20/1M
Key Cost Levers & Architecture
Practical mechanisms to reduce inference costs with Qwen3 Next 80B A3B on AWSPrompt CachingSave ~75%
Caches repetitive system instructions, schemas, and document prefixes in memory with 5-minute and extended 1-hour TTL tiers.
- Read Rate: $0.04 / 1M tokens
- Write Rate (5m TTL): $0.18 / 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: $0.60 / 1M tokens
- Ideal for: Offline classification, synthetic data generation, benchmark evals
Cross-Region & Tiers13 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 13 available AWS cloud regionsBaseline: $0.14/1M inGovCloud: $0.22/1M in13 Global Regions
| AWS Region | Prompt Input $/1M | Completion Output $/1M | Cache Read $/1M | Batch Input $/1M | Pricing Tier |
|---|---|---|---|---|---|
| us-east-1 US East (N. Virginia) | $0.14 | $1.20 | โ | $0.07 | Baseline |
| us-west-2 US West (Oregon) | $0.14 | $1.20 | โ | $0.07 | Baseline |
| eu-central-1 EU (Frankfurt) | $0.17 | $1.44 | โ | $0.08 | +20% vs Baseline |
| eu-west-1 EU (Ireland) | $0.17 | $1.44 | โ | $0.08 | +20% vs Baseline |
| ap-northeast-1 Asia Pacific (Tokyo) | $0.17 | $1.44 | โ | $0.08 | +20% vs Baseline |
| ap-southeast-3 Asia Pacific (Jakarta) | $0.17 | $1.44 | โ | $0.08 | +20% vs Baseline |
| ap-south-1 Asia Pacific (Mumbai) | $0.17 | $1.41 | โ | $0.08 | +20% vs Baseline |
| ap-southeast-2 Asia Pacific (Sydney) | $0.14 | $1.24 | โ | $0.07 | +3% vs Baseline |
| eu-west-2 EU (London) | $0.22 | $1.86 | โ | $0.11 | +55% vs Baseline |
| eu-south-1 EU (Milan) | $0.17 | $1.44 | โ | $0.08 | +20% vs Baseline |
| eu-north-1 EU (Stockholm) | $0.17 | $1.44 | โ | $0.08 | +20% vs Baseline |
| sa-east-1 South America (Sao Paulo) | $0.17 | $1.44 | โ | $0.08 | +20% vs Baseline |
| us-east-2 US East (Ohio) | $0.14 | $1.20 | โ | $0.07 | Baseline |
No AWS regions found matching your filter.
Developer Quickstart
Invoke Qwen3 Next 80B A3B 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="alibaba.qwen3-next-80b-a3b-v1:0",
messages=[
{
"role": "user",
"content": [{"text": "Summarize key features and cost levers of Qwen3 Next 80B A3B."}]
}
],
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 Qwen3 Next 80B A3B with Alternatives
Open Multi-Model Estimator →Qwen3 Next 80B A3B vsJamba 1.5 LargeAI21 Labs
Input Rate:$2.00/1M
Output Rate:$8.00/1M
Qwen3 Next 80B A3B vsJamba 1.5 MiniAI21 Labs
Input Rate:$0.20/1M
Output Rate:$0.40/1M
Qwen3 Next 80B A3B vsJamba-InstructAI21 Labs
Input Rate:$0.50/1M
Output Rate:$0.70/1M