GPT-3.5 Turbo

GPT-3.5 Turbo

OpenAILLM

GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks. Training data up to Sep 2021.

API AvailableTool Calling

Specifications

Context Window

16K tokens

Input Price/1M

$0.50

Output Price/1M

$1.50

Parameters

Max Output

4K tokens

Benchmarks

GPT-3.5 Turbo results on the main AI model evaluation benchmarks. Higher scores indicate better performance.

Coding

BenchmarkScoreMaximumMethodology
AA Coding Index10.7100.0Artificial Analysis official API

Knowledge

BenchmarkScoreMaximumMethodology
MMLU-Pro46.0100.0

Math

BenchmarkScoreMaximumMethodology
MATH-50044.1100.0Artificial Analysis official API

overall

BenchmarkScoreMaximumMethodology
AA Intelligence Index9.0100.0Artificial Analysis official API

Reasoning

BenchmarkScoreMaximumMethodology
MMLU Pro46.2100.0Artificial Analysis official API
GPQA Diamond29.7100.0Artificial Analysis official API

Information

Release date
May 28, 2023
Tool Calling
✅ Supported
Vision
❌ Not supported
Audio
❌ Not supported

Full Analysis: GPT-3.5 Turbo

What is GPT-3.5 Turbo?

GPT-3.5 Turbo is an AI model developed by OpenAI, classified as a large language model (LLM). It focuses on text processing and natural language generation. As a proprietary model, it is available via OpenAI's cloud API. With a context window of 16K tokens, it is suitable for processing short documents and direct prompts.

Pricing & Costs in 2026

GPT-3.5 Turbo is usage-based, priced at $0.5/1M input tokens and $1.5/1M 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

GPT-3.5 Turbo was evaluated on 6 different benchmarks, covering categories like Coding, Knowledge, Math, 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

GPT-3.5 Turbo is suitable for a wide range of AI applications: automation with tool calling (API integration, databases, external systems), high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.

Comparison with Alternatives

In the 2026 AI model ecosystem, GPT-3.5 Turbo competes directly with similarly capable models. Key competitors include Claude (Anthropic), Gemini (Google), and open source models like Llama (Meta) and Qwen (Alibaba). 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 GPT-3.5 Turbo?

GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks. Training data up to Sep 2021.

How much does GPT-3.5 Turbo cost?

GPT-3.5 Turbo costs $0.5/1M input tokens and $1.5/1M 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 GPT-3.5 Turbo compare with other models?

In available benchmarks, GPT-3.5 Turbo scored: AA Coding Index: 10.7/100, MMLU-Pro: 46/100, MATH-500: 44.1/100. See the full table above for a detailed comparison.

Is GPT-3.5 Turbo open source?

No, GPT-3.5 Turbo is a proprietary model from OpenAI. It is available via cloud API. For open source alternatives, check our open source model ranking.

What is GPT-3.5 Turbo best for?

GPT-3.5 Turbo excels at general-purpose language tasks. It supports tool calling for API integrations and automation.

Last updated: June 01, 2026 View methodology →