Qwen-Omni Turbo Realtime API Pricing

Alibaba · released May 8, 2025 · 33K context · API model ID qwen-omni-turbo-realtime

Qwen-Omni Turbo Realtime by Alibaba API pricing: $0.27 per 1M input tokens and $1.07 per 1M output tokens (provider list price via models.dev, Oct 10, 2026).

Prices

Qwen-Omni Turbo Realtime prices, USD per 1M tokens
PriceUSD per 1M tokens
Input$0.27
Output$1.07
Cache readNot published
Cache writeNot published
Audio input$4.44
Audio output$8.89

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

$241.50

per month

per day
$8.05
per request
$0.000805

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$241.50/mo
RAG8,000 in / 500 out tokens, 5,000 requests a day$404.25/mo
Coding agent50,000 in / 2,000 out tokens, 1,000 requests a day, 80% cached input$469.20/mo

Context and capabilities

Context
32,768 tokens
Max output
2,048 tokens
Input
text, image, audio
Output
text, audio
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-Omni Turbo Realtime cost per month?
For a chatbot handling 10,000 requests a day with 1,000 input and 500 output tokens each, Qwen-Omni Turbo Realtime costs about $241.50 per month at Alibaba's list prices ($0.27 per 1M input tokens, $1.07 per 1M output tokens).
Does Qwen-Omni Turbo Realtime support prompt caching?
No cache read price is published for Qwen-Omni Turbo Realtime.
How long is Qwen-Omni Turbo Realtime's context window?
Qwen-Omni Turbo Realtime accepts up to 32,768 tokens (33K) of context and returns up to 2,048 tokens per response.