Specifications
Context Window
131K tokens
Input Price/1M
$0.05
Output Price/1M
$0.20
Parameters
—
Speed
108 tok/s
Latency (TTFT)
2.2s
Max Output
8K tokens
Benchmarks
Qwen: Qwen-Turbo results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 16.0 | 100.0 | — |
| SciCode | 15.0 | 100.0 | — |
Knowledge
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 63.0 | 100.0 | — |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 6.0 | 100.0 | — |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| GPQA Diamond | 41.0 | 100.0 | — |
| HLE | 4.0 | 100.0 | — |
Information
- Release date
- November 18, 2024
- Tool Calling
- ❌ Not supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: Qwen: Qwen-Turbo
What is Qwen: Qwen-Turbo?
Qwen: Qwen-Turbo is an AI model developed by Alibaba, classified as a large language model (LLM). It focuses on text processing and natural language generation. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 131K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
Qwen: Qwen-Turbo is usage-based, priced at $0.05/1M input tokens and $0.2/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Benchmarks & Performance
Qwen: Qwen-Turbo was evaluated on 6 different benchmarks, covering categories like Coding, Knowledge, overall, Reasoning. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
Qwen: Qwen-Turbo is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, Qwen: Qwen-Turbo competes directly with similarly capable models. Alibaba competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is Qwen: Qwen-Turbo?
Qwen: Qwen-Turbo is an AI model developed by Alibaba. It is a language model (LLM), open source.
How much does Qwen: Qwen-Turbo cost?
Qwen: Qwen-Turbo costs $0.05/1M input tokens and $0.2/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does Qwen: Qwen-Turbo compare with other models?
In available benchmarks, Qwen: Qwen-Turbo scored: LiveCodeBench: 16/100, SciCode: 15/100, MMLU-Pro: 63/100. See the full table above for a detailed comparison.
Is Qwen: Qwen-Turbo open source?
Yes, Qwen: Qwen-Turbo is an open source model. You can deploy it on-premises, customize it via fine-tuning, and maintain full control over your data. Check the official repository for the specific license.
What is Qwen: Qwen-Turbo best for?
Qwen: Qwen-Turbo excels at general-purpose language tasks. With its large context window, it handles long documents, codebases, and extended conversations.
Last updated: August 10, 2026 • View methodology →