Qwen API Pricing Calculator
Estimate your monthly and annual Alibaba Cloud Qwen API costs based on token volume, model tier, context length, caching, and workload type. Built for developers working with Qwen-Turbo, Qwen-Plus, Qwen-Max, Qwen-Long, and multimodal Qwen-VL models via DashScope.
Estimate Your Qwen API Cost
Configure your expected monthly usage below
A strong balance of intelligence and speed for most production application workloads.
Affects per-request token estimates shown in the results.
Your prompts, system messages, conversation history, and documents sent to the API.
Text, code, maths, or answers generated by Qwen in response to your prompts.
Reuses repeated prefixes like system prompts or large documents at a lower rate. Highly effective for RAG pipelines and agent workflows.
The portion of input tokens served from cache. Billed at the cache read rate — typically 80–90% cheaper than full input.
Enable if using Qwen-VL for image understanding, chart reading, visual Q&A, or document OCR tasks.
Used to calculate average cost per API call and validate your token estimates.
Cost Estimate
Monthly & annual Qwen API spend
Select your Qwen model, configure your expected token volumes, and click Calculate to see your estimated monthly API cost.
Qwen2.5 Model Rates & Specs
Indicative per-token rates and specifications for Alibaba Cloud Qwen API model tiers in 2026 via DashScope. All prices in USD per million tokens (MTok).
| Model | Input ($/MTok) | Output ($/MTok) | Cache Read ($/MTok) | Context | Best For |
|---|---|---|---|---|---|
| Qwen-Turbo Free tier | $0.05 | $0.20 | $0.005 | 1M tokens | High-volume automation, fast completions |
| Qwen-Plus | $0.40 | $1.20 | $0.04 | 131K tokens | Everyday apps, chat, RAG, code review |
| Qwen-Max | $1.60 | $6.40 | $0.16 | 32K tokens | Complex reasoning, high-accuracy tasks |
| Qwen-Long | $0.05 | $0.20 | $0.005 | 1M tokens | Books, large codebases, long docs |
| Qwen-VL (Vision) | $0.80 | $0.80 | $0.08 | 32K tokens | Image understanding, charts, OCR |
| Qwen2.5-Coder | $0.40 | $1.20 | $0.04 | 131K tokens | Code generation, debugging, refactoring |
| Qwen2.5-Math | $0.40 | $1.20 | $0.04 | 4K tokens | Maths reasoning, scientific computation |
* Rates are indicative estimates for planning purposes. Always verify current pricing via the official Alibaba Cloud DashScope platform.
Qwen API Pricing FAQ
Everything developers need to know about Qwen API costs, token usage, caching, and model selection for 2026.
The Qwen API is provided by Alibaba Cloud via the DashScope platform, giving developers programmatic access to the Qwen2.5 family of large language models. Qwen models are optimised for multilingual tasks across Chinese and English, as well as code generation, mathematical reasoning, long-context understanding, and multimodal inputs including images and audio. The API is OpenAI-compatible, making migration from other providers straightforward.
Qwen API costs are based on the total number of tokens processed per request — both input tokens (your prompts, system messages, and context) and output tokens (the model’s generated response). Costs are denominated per million tokens (MTok). On premium tiers like Qwen-Max, output tokens are priced higher than input tokens. Context caching provides substantial savings for repeated context.
Alibaba Cloud offers a wide range of tiers: Qwen-Turbo for fast, cost-efficient high-volume tasks; Qwen-Plus for balanced everyday production use; Qwen-Max for the highest reasoning quality; Qwen-Long for ultra-extended 1M token context windows; Qwen-VL for multimodal vision tasks; and specialist models Qwen2.5-Coder and Qwen2.5-Math optimised for software engineering and mathematics respectively.
A token is roughly 3–4 characters of English text or approximately 1.5–2 Chinese characters. One thousand tokens equates to approximately 750 English words or a medium-length article. Because Qwen is natively optimised for Chinese, token efficiency for Chinese text is higher than many English-first models — though Chinese-heavy workloads may still produce more tokens per equivalent semantic content.
Context caching stores repeated prefixes — like system prompts, large documents, or codebase context — so they are not re-processed on every request. Cached input tokens are billed at the cache read rate, typically 80–90% cheaper than the standard input rate. For RAG pipelines, agent workflows, or apps with large consistent system prompts, caching can dramatically reduce monthly costs. Qwen-Turbo and Qwen-Long offer the lowest cache read rates.
Qwen-Long supports context windows of up to 1 million tokens, making it one of the largest commercially available context windows. This enables processing entire books, large repositories, or extensive document collections in a single request. Qwen-Turbo and Qwen-Plus also support extended contexts up to 1M and 131K tokens respectively — suitable for most enterprise RAG and long-document tasks.
The most impactful cost reduction strategies are: 1) Enable context caching for any repeated system prompt or document context. 2) Route high-volume simple tasks to Qwen-Turbo, the lowest-cost tier. 3) Use Qwen2.5-Coder or Qwen2.5-Math for specialist tasks rather than general-purpose Qwen-Max. 4) Set max_tokens limits to cap output length. 5) Truncate conversation history aggressively in chat applications. 6) Reserve Qwen-Long only when extended context is genuinely required.
Yes. Alibaba Cloud typically provides free trial tokens for new DashScope accounts, and Qwen-Turbo has historically included a free usage quota for eligible users. Free tier limits and eligibility change regularly — always check the official DashScope platform for current free quota details before planning your budget.