Qwen Plus Character (Japanese) API Pricing

Alibaba · released January 2024 · 8.2K context · API model ID qwen-plus-character-ja

Qwen Plus Character (Japanese) by Alibaba API pricing: $0.50 per 1M input tokens and $1.40 per 1M output tokens (provider list price via models.dev, Oct 10, 2026).

Prices

Qwen Plus Character (Japanese) prices, USD per 1M tokens
PriceUSD per 1M tokens
Input$0.50
Output$1.40
Cache readNot published
Cache writeNot published

Alibaba's list price for its own API, as compiled by models.dev and checked Oct 10, 2026, 09:00 UTC. Prices on cloud platforms and resellers can differ. Provider documentation

Estimated monthly cost

$360.00

per month

per day
$12.00
per request
$0.0012

Cost = input tokens × input price + output tokens × output price, 30 days a month. Cached input uses the cache read price. Cache write fees are not included.

Compare this workload across models

Monthly cost by workload

WorkloadPer month
Chatbot1,000 in / 500 out tokens, 10,000 requests a day$360.00/mo
RAG8,000 in / 500 out tokens, 5,000 requests a day$705.00/mo
Coding agent50,000 in / 2,000 out tokens, 1,000 requests a day, 80% cached input$834.00/mo

Context and capabilities

Context
8,192 tokens
Max output
512 tokens
Input
text
Output
text
Knowledge cutoff
April 2024
Open weights
No
Tool calling
Yes
Reasoning
No
Structured outputs
No

Capabilities and limits as listed by models.dev.

Similarly priced models

Price history

No price changes since we started tracking on Oct 8, 2026.

Questions

How much does Qwen Plus Character (Japanese) cost per month?
For a chatbot handling 10,000 requests a day with 1,000 input and 500 output tokens each, Qwen Plus Character (Japanese) costs about $360.00 per month at Alibaba's list prices ($0.50 per 1M input tokens, $1.40 per 1M output tokens).
Does Qwen Plus Character (Japanese) support prompt caching?
No cache read price is published for Qwen Plus Character (Japanese).
How long is Qwen Plus Character (Japanese)'s context window?
Qwen Plus Character (Japanese) accepts up to 8,192 tokens (8.2K) of context and returns up to 512 tokens per response.