LangMart: Qwen: Qwen-Turbo
Model Overview
| Property | Value |
|---|---|
| Model ID | openrouter/qwen/qwen-turbo |
| Name | Qwen: Qwen-Turbo |
| Provider | qwen |
| Released | 2025-02-01 |
Description
Qwen-Turbo, based on Qwen2.5, is a 1M context model that provides fast speed and low cost, suitable for simple tasks.
Description
LangMart: Qwen: Qwen-Turbo is a language model provided by qwen. This model offers advanced capabilities for natural language processing tasks.
Provider
qwen
Specifications
| Spec | Value |
|---|---|
| Context Window | 1,000,000 tokens |
| Modalities | text->text |
| Input Modalities | text |
| Output Modalities | text |
Pricing
| Type | Price |
|---|---|
| Input | $0.05 per 1M tokens |
| Output | $0.20 per 1M tokens |
Capabilities
- Max tokens
- Presence penalty
- Response format
- Seed
- Temperature
- Tool choice
- Tools
- Top p
Detailed Analysis
Qwen-Turbo is the speed-optimized model in Alibaba Cloud's commercial Qwen API lineup, designed for applications prioritizing low latency and cost efficiency. Note: This model is deprecated and will no longer receive updates - users should migrate to Qwen-Flash for the latest speed-optimized capabilities. Key characteristics: (1) Architecture: Lightweight dense transformer optimized for inference speed, with reduced parameter count compared to Plus/Max variants; (2) Performance: Suitable for simple tasks, quick responses, and high-throughput scenarios where sub-second latency is critical; (3) Use Cases: Real-time chat applications, simple Q&A, content classification, sentiment analysis, rapid prototyping, and high-volume simple inference tasks; (4) Context Window: Standard context support (typically 8K tokens); (5) Pricing: Most cost-effective tier in the Qwen API family, optimized for high-volume usage; (6) Trade-offs: Limited reasoning capability compared to Plus/Max, not suitable for complex multi-step tasks, being phased out in favor of Qwen-Flash. Best for legacy applications or simple tasks requiring fast response times, but new deployments should use Qwen-Flash instead.