---
title: Qwen2.5 72B Instruct Turbo — Fast LLM | ModelsLab
description: Access Qwen2.5 72B Instruct Turbo API for rapid instruction following, coding, and math tasks. Generate high-quality outputs at 35 tokens per second. Tr...
url: https://modelslab.com/qwen25-72b-instruct-turbo
canonical: https://modelslab.com/qwen25-72b-instruct-turbo
type: website
component: Seo/ModelPage
generated_at: 2026-04-15T02:04:59.239811Z
---

Available now on ModelsLab · Language Model

Qwen2.5 72B Instruct Turbo
Turbocharge Qwen2.5 72B
---

[Try Qwen2.5 72B Instruct Turbo](/models/qwen/Qwen-Qwen2.5-72B-Instruct-Turbo) [API Documentation](https://docs.modelslab.com)

Run Turbo. Scale Fast.
---

Turbo Speed

### 35 Tokens Per Second

Qwen2.5 72B Instruct Turbo hits 35 output tokens per second with 32K context.

Precision Tasks

### Superior Instruction Following

Handles complex coding, math, and structured JSON outputs reliably.

Efficient Context

### 32K Token Window

Reduced from 128K for faster inference on Qwen2.5 72B Instruct Turbo API.

Examples

See what Qwen2.5 72B Instruct Turbo can create
---

Copy any prompt below and try it yourself in the [playground](/models/qwen/Qwen-Qwen2.5-72B-Instruct-Turbo).

Code Generator

“Write a Python function to parse JSON data from a REST API, handle errors, and return structured output as a Pandas DataFrame. Include type hints and docstring.”

Math Solver

“Solve this equation step-by-step: Find x in 3x^2 + 5x - 2 = 0 using quadratic formula. Explain each step and verify the solution.”

JSON Formatter

“Convert this unstructured text into valid JSON schema: User data includes name, age 30, city Tokyo, skills Python JavaScript. Ensure strict JSON output.”

Instruction Chain

“You are a coding assistant. First analyze the problem, then write Rust code for a binary search tree insertion, and finally add unit tests.”

For Developers

A few lines of code.
Turbo LLM. One Call.
---

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

- **Serverless:** scales to zero, scales to millions
- **Pay per token,** no minimums
- **Python and JavaScript SDKs,** plus REST API

[API Documentation ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())</code>
```

FAQ

Common questions about Qwen2.5 72B Instruct Turbo
---

[Read the docs ](https://docs.modelslab.com)

### What is Qwen2.5 72B Instruct Turbo?

### How fast is qwen2 5 72b instruct turbo?

### What is Qwen2.5 72B Instruct Turbo context window?

### Does Qwen2.5 72B Instruct Turbo API support function calling?

### Is Qwen2.5 72B Instruct Turbo a good alternative?

### What are qwen2 5 72b instruct turbo api benchmarks?

Ready to create?
---

Start generating with Qwen2.5 72B Instruct Turbo on ModelsLab.

[Try Qwen2.5 72B Instruct Turbo](/models/qwen/Qwen-Qwen2.5-72B-Instruct-Turbo) [API Documentation](https://docs.modelslab.com)

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*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

---
*Generated by ModelsLab - 2026-04-15*