The Qwen3 Flash model offers a powerful fusion of thinking and non-thinking modes with dynamic in-conversation switching, excelling in complex reasoning while showing significant gains in instruction following and text comprehension. It supports a 1M context length and is billed on a tiered model corresponding to context usage. This model version is functionally equivalent to the snapshot model qwen-flash-2025-07-28.
Inference Service Provider
The inference service provider for qwen-flash is QwenCloud.
Model Capabilities
- Singapore
- China North 2 (Beijing)
- Germany (Frankfurt)
- US (Virginia)
| Capability | Support | Capability | Support |
|---|---|---|---|
Input Modality | Text | Output Modality | Text |
Model Experience | Supported | Function Calling | Unsupported |
Structured Outputs | Supported | Web Search | Unsupported |
Prefix Completion | Supported | Context Caching | Supported |
Batch Inference | Unsupported | Fine-tuning | Unsupported |
Context Limits
| Parameter | Value | Parameter | Value |
|---|---|---|---|
Max Input Length | 997952 | Max Output Length | 32768 |
Context Window | 1000000 |
Pricing
This page only shows the original pricing for model API calls, excluding any limited-time promotions. Visit QwenCloud console for promotional offers.
- Singapore
- China North 2 (Beijing)
- Germany (Frankfurt)
- US (Virginia)
Input<=256k
Input<=256k
| Billing Item | Price (USD) | Unit |
|---|---|---|
Input | 0.05 | Per 1M tokens |
Output | 0.4 | Per 1M tokens |
Input(Implicit Cache) | 0.01 | Per 1M tokens |
Input(Batch File) | 0.025 | Per 1M tokens |
Output(Batch File) | 0.2 | Per 1M tokens |
Explicit Cache Creation | 0.063 | Per 1M tokens |
Explicit Cache Read | 0.005 | Per 1M tokens |
256k<Input<=1m
256k<Input<=1m
| Billing Item | Price (USD) | Unit |
|---|---|---|
Input | 0.25 | Per 1M tokens |
Output | 2 | Per 1M tokens |
Input(Implicit Cache) | 0.05 | Per 1M tokens |
Input(Batch File) | 0.125 | Per 1M tokens |
Output(Batch File) | 1 | Per 1M tokens |
Explicit Cache Creation | 0.313 | Per 1M tokens |
Explicit Cache Read | 0.025 | Per 1M tokens |
Rate Limits
- Singapore
- China North 2 (Beijing)
- Germany (Frankfurt)
- US (Virginia)
| Parameter | Value |
|---|---|
RPM (Requests Per Minute) | 600 |
TPM (Tokens Per Minute) | 5,000,000 |
Snapshot Versions
qwen-flash-2025-07-28
The Qwen3 Flash model (snapshot 2025-07-28) offers a powerful fusion of thinking and non-thinking modes with dynamic in-conversation switching, excelling in complex reasoning while showing significant gains in instruction following and text comprehension. It supports a 1M context length and is billed on a tiered model corresponding to context usage.
Inference Service Provider
The inference service provider for qwen-flash-2025-07-28 is QwenCloud.
Model Capabilities
- Singapore
- China North 2 (Beijing)
- Germany (Frankfurt)
- US (Virginia)
| Capability | Support | Capability | Support |
|---|---|---|---|
Input Modality | Text | Output Modality | Text |
Model Experience | Supported | Function Calling | Unsupported |
Structured Outputs | Supported | Web Search | Unsupported |
Prefix Completion | Supported | Context Caching | Unsupported |
Batch Inference | Unsupported | Fine-tuning | Unsupported |
Context Limits
| Parameter | Value | Parameter | Value |
|---|---|---|---|
Max Input Length | 997952 | Max Output Length | 32768 |
Context Window | 1000000 |
Pricing
This page only shows the original pricing for model API calls, excluding any limited-time promotions. Visit QwenCloud console for promotional offers.
- Singapore
- China North 2 (Beijing)
- Germany (Frankfurt)
- US (Virginia)
Input<=256k
Input<=256k
| Billing Item | Price (USD) | Unit |
|---|---|---|
Input | 0.05 | Per 1M tokens |
Output | 0.4 | Per 1M tokens |
256k<Input<=1m
256k<Input<=1m
| Billing Item | Price (USD) | Unit |
|---|---|---|
Input | 0.25 | Per 1M tokens |
Output | 2 | Per 1M tokens |
Rate Limits
- Singapore
- China North 2 (Beijing)
- Germany (Frankfurt)
- US (Virginia)
| Parameter | Value |
|---|---|
RPM (Requests Per Minute) | 600 |
TPM (Tokens Per Minute) | 5,000,000 |