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Qwen2.5 72B Instruct TurboTurbocharge Qwen2.5 72B

Try Qwen2.5 72B Instruct TurboAPI Documentation

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.

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 
import requests


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

FAQ

Common questions about Qwen2.5 72B Instruct Turbo

Read the docs

Qwen2.5 72B Instruct Turbo is a speed-optimized variant of Alibaba's 72B LLM. It reduces context to 32K tokens from 128K for faster performance. Delivers strong coding and math results.

Achieves 35 tokens per second output speed. Latency averages 3.2 seconds. Outpaces models like Llama 3.1 in balanced quality-speed tasks.

Supports 32K tokens maximum, optimized for efficiency. Standard Qwen2.5 72B Instruct uses 128K. Ideal for tasks under full context needs.

Yes, includes function calling and JSON schema support. No vision or audio modalities. Text-only with system messages enabled.

Serves as fast Qwen2.5 72B Instruct Turbo alternative for speed-critical apps. Open-source under Apache 2.0. Quality index at 75 with multilingual support.

MMLU-Pro at 0.7, MATH-500 at 0.9, coding index 11.9. Time to first token 1.13s. Excels in instruction following and agent workflows.

Ready to create?

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

Try Qwen2.5 72B Instruct TurboAPI Documentation