qwen-turbo

qwen-turbo is a budget-tier language model from Alibaba Cloud. qwen-turbo is a proprietary model available exclusively through Alibaba Cloud's API. Qwen is Alibaba's open-weights model family, with strong multilingual performance (especially Chinese/English) and a wide parameter range from 0.5B to 72B.

qwen-turbo is priced at $0.05/1M input tokens and $0.2/1M output tokens. Output tokens are 4× more expensive than input tokens — this ratio reflects the sequential nature of autoregressive generation, which requires a separate forward pass per output token versus parallel processing of all input tokens simultaneously. At a typical usage pattern of 1,000 input tokens and 500 output tokens per call, qwen-turbo costs approximately $0.15 per 1,000 API calls. Alibaba Cloud does not publish a prompt caching rate for this model, so repeated long contexts are billed at the standard $0.05/1M input rate.

Its 131K-token context window handles most long-document tasks — roughly 75,000 words or a full novel — without requiring chunking or retrieval augmentation. Median latency (P50 time-to-first-token) is approximately 200ms — fast enough for real-time interactive applications. Throughput is approximately 400 tokens/second — fast enough to stream responses at reading speed with headroom for concurrent requests. Maximum output length is 8K tokens — adequate for most generation tasks including essays, code functions, and detailed responses.

qwen-turbo is best suited to cost, speed. Supported capabilities include function calling / tool use for agentic workflows, streaming token output for real-time UIs. Function calling support makes it suitable for building AI agents, structured data extraction pipelines, and any workflow requiring the model to invoke external APIs or return typed JSON. When evaluating this model for a specific workload, the most important factors are: context window (does your input fit?), output price (how long are your generations?), and latency (is this interactive or batch?). The pricing table above shows how qwen-turbo compares to similar models across these dimensions.

qwen-turbo sits in the budget tier — the most cost-efficient models, best for high-volume simple tasks, classification, extraction, and applications where cost per call is the primary constraint. Unlike open-weights alternatives, qwen-turbo is only available via Alibaba Cloud's API — there is no self-hosted option, which simplifies deployment but creates vendor dependency. When comparing qwen-turbo to alternatives, use the similar models section on this page to find models at comparable price points with different capability tradeoffs. The intelligence score (50/100) reflects aggregate benchmark performance — a useful proxy for general capability, though real-world performance varies significantly by task type. Always test with your specific prompts and use case before committing to a model for production.