---
title: GPT-3.5 Turbo Instruct — Instruction LLM | ModelsLab
description: Access OpenAI: GPT-3.5 Turbo Instruct API for precise instruction following and text completion. Generate code and content via completions endpoint. Try...
url: https://modelslab.com/openai-gpt-35-turbo-instruct
canonical: https://modelslab.com/openai-gpt-35-turbo-instruct
type: website
component: Seo/ModelPage
generated_at: 2026-05-07T09:49:04.880377Z
---

Available now on ModelsLab · Language Model

OpenAI: GPT-3.5 Turbo Instruct
Instruct Precisely. Complete Fast
---

[Try OpenAI: GPT-3.5 Turbo Instruct](/models/open_router/openai-gpt-3.5-turbo-instruct) [API Documentation](https://docs.modelslab.com)

Execute Instructions Efficiently
---

Task Precision

### Follows Instructions Directly

Handles specific commands via completions endpoint for OpenAI: GPT-3.5 Turbo Instruct API.

Low Hallucinations

### Reduces Errors Toxicity

Delivers truthful responses in OpenAI: GPT-3.5 Turbo Instruct model with 4K context window.

Cost Efficient

### Matches GPT-3.5 Performance

Provides question-answering and text completion as OpenAI: GPT-3.5 Turbo Instruct alternative.

Examples

See what OpenAI: GPT-3.5 Turbo Instruct can create
---

Copy any prompt below and try it yourself in the [playground](/models/open_router/openai-gpt-3.5-turbo-instruct).

Photosynthesis Quiz

“Create a multiple-choice quiz question on photosynthesis with four options and correct answer explanation.”

Research Hypothesis

“Generate a research hypothesis about social media impact on mental health, including variables and predicted outcomes.”

Lesson Plan

“Generate detailed lesson plan on renewable energy with objectives, activities, assessments, and discussion topics.”

Code Snippet

“Write Python function to calculate Fibonacci sequence up to n terms using recursion with memoization.”

For Developers

A few lines of code.
Completions. One prompt.
---

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 OpenAI: GPT-3.5 Turbo Instruct
---

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

### What is OpenAI: GPT-3.5 Turbo Instruct?

GPT-3.5 Turbo Instruct excels at following instructions via completions endpoint. It uses 4,096 token context and max output. Training data ends September 2021.

### How does openai gpt 3.5 turbo instruct differ from chat models?

It focuses on task-oriented completions, not conversations. Use completions API, not chat completions. Reduces hallucinations for precise outputs.

### What is OpenAI: GPT-3.5 Turbo Instruct API pricing?

Input costs $1.50 per 1M tokens. Output costs $2.00 per 1M tokens. Matches GPT-3.5 efficiency.

### Is OpenAI: GPT-3.5 Turbo Instruct model good for code generation?

Yes, generates code and handles tasks like code review. Compatible with legacy completions endpoint.

### Why use OpenAI: GPT-3.5 Turbo Instruct alternative?

Offers same performance as GPT-3.5 at lower cost for instruct tasks. Ideal for non-chat workloads.

### What is the context window for openai gpt 3.5 turbo instruct api?

Supports 4,096 input tokens and 4,096 max output tokens. Optimized for instruction following.

Ready to create?
---

Start generating with OpenAI: GPT-3.5 Turbo Instruct on ModelsLab.

[Try OpenAI: GPT-3.5 Turbo Instruct](/models/open_router/openai-gpt-3.5-turbo-instruct) [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)

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*Generated by ModelsLab - 2026-05-07*