Qwen2.5 Turbo
Qwen2.5 Turbo is a chat model from Alibaba in the Qwen2.5 family, positioned as a speed- and cost-oriented option within that generation.
API Pricing
Cheapest on Deep Infra — 38% below avg| Provider | Input / 1M | Output / 1M |
|---|---|---|
| $0.360 | $0.400 | |
| $0.800 | $0.800 |
Prices updated daily. Last check: Sep 3, 2026
Qwen2.5 Turbo pricing by provider
Input, output, and batch rates, plus alternatives, for one provider at a time.
Performance & Benchmarks
Source: Artificial Analysis →Reasoning & Knowledge
- MMLU-Pro63.3%
- GPQA Diamond41.0%
- Humanity's Last Exam4.1%
Coding
- LiveCodeBench16.3%
- SciCode15.3%
Math
- AIME12.0%
- MATH-50080.5%
Benchmarks measured Sep 2026. Scores are independent evaluations, not vendor-reported.
Model Details
General
- Creator
- Alibaba
- Modalities
- Text
Capabilities
- Tool Calling
- No
- Open Source
- No
Strengths & Limitations
Strengths
- Part of Alibaba's Qwen2.5 generation, a family with wide provider and tooling support
- Turbo positioning targets high-request-volume text workloads rather than maximum capability
- Available as a hosted API, so no GPU provisioning or model serving is required
- Qwen models generally have strong Chinese-language coverage alongside English, useful for bilingual deployments
- Sits alongside other Qwen2.5 variants, making it straightforward to move up or down the family if capability needs change
- Chat-formatted interface fits standard OpenAI-style client libraries used by most providers
Limitations
- We do not have a confirmed context window recorded for this variant in our database
- Throughput and time-to-first-token figures we track are not currently populated, so measured speed data is unavailable here
- Turbo-tier models generally trade depth on complex reasoning for lower cost and faster responses
- Multimodal input support is not something we have confirmed for this entry
- Provider availability for Qwen2.5 Turbo is narrower than for the open-weight Qwen2.5 checkpoints
Key Features
About Qwen2.5 Turbo
Common Use Cases
Qwen2.5 Turbo suits high-volume text workloads where per-request cost and response latency dominate the decision: customer-facing chat assistants, ticket triage and routing, document summarization, structured field extraction from free text, content classification, and bulk translation or rewriting between English and Chinese. It is a reasonable default for pipelines that issue thousands of similar short requests, where a larger Qwen2.5 variant would add cost without changing outcomes. For tasks that require long multi-step reasoning, difficult code generation, or agentic tool loops with many turns, evaluate a higher-tier Qwen2.5 model or a dedicated reasoning model and compare quality on your own test set before committing.
Frequently Asked Questions
How much does Qwen2.5 Turbo cost?
Pricing depends on which provider serves the model and on the pricing type — input versus output tokens, batch versus real-time, and any cached-input discounts. Rates also change over time. Check the pricing table on this page for the current per-provider figures rather than relying on a fixed number.
What is Qwen2.5 Turbo best used for?
High-frequency text tasks where cost and speed matter more than maximum reasoning depth — chat assistants, summarization, extraction, classification, and English/Chinese translation work. Its Turbo positioning within the Qwen2.5 family signals a throughput-oriented variant rather than the family's heaviest option.
How does Qwen2.5 Turbo differ from other Qwen2.5 models?
Qwen2.5 spans many variants, including open-weight checkpoints at several parameter counts and larger hosted models. Turbo is the throughput- and cost-oriented hosted variant. Larger siblings generally perform better on hard reasoning and code tasks, while Turbo aims to serve more requests for less.
What context window does Qwen2.5 Turbo support?
We do not have a confirmed context window recorded for this variant in our database, and Alibaba has shipped different context configurations across Qwen2.5 endpoints. Verify the current limit in Alibaba's model documentation or with the specific provider you plan to use.
Does Qwen2.5 Turbo accept image input?
We do not track confirmed multimodal input for this entry. Alibaba publishes separate Qwen-VL models for vision tasks. If you need image understanding, check the provider's documentation for the exact endpoint or consider a Qwen vision variant.
How fast is Qwen2.5 Turbo?
The throughput and time-to-first-token measurements we track from Artificial Analysis are not populated for this model, so we cannot quote figures here. Speed also varies substantially by provider, region, and load, so benchmark on your own traffic pattern.