GPT-3.5 vs. GPT-4: Biggest differences to consider
GPT-3.5 or GPT-4? With multiple OpenAI language models to choose from, picking the right option for your organization's needs comes down to the details.
With a growing number of underlying model options for OpenAI's ChatGPT, choosing the right one is a necessary first step for any AI project. Knowing the differences between GPT-3, GPT-3.5 and GPT-4 is essential when purchasing SaaS-based generative AI tools.
GPT-3.5, the refined version of GPT-3 rolled out in November 2022, is currently offered in ChatGPT's free web app version and its premium Turbo API versions. GPT-4, released in March 2023, provides an even more advanced GPT choice for workplace tasks and comes with its own Turbo version. Turbo versions represent incremental improvements, such as lower latency and minor bug fixes.
Choosing between GPT-3.5 and GPT-4 means parsing out the differences in their respective features. By breaking down the two models' key differences in capabilities, accuracy and pricing, organizations can decide which OpenAI GPT model is right for them.
GPT-3.5 vs. GPT-4: The major differences
GPT-3.5 and GPT-4 are both versions of OpenAI's generative pre-trained transformer model, which powers the ChatGPT app. They're currently available to the public with a range of capabilities, features and price points.
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Extended capabilities
The difference in capabilities between GPT-3.5 and GPT-4 indicates OpenAI's interest in advancing the features of its models to meet increasingly complex use cases across industries.
GPT-3.5
GPT-3.5 has the following key capabilities:
- Understands and generates humanlike text using natural language comprehension and generation to complete various natural language-related tasks.
- Translates text from one language to another with some fluency and accuracy.
- Answers questions by providing relevant information, making it suitable for chatbots and virtual assistants using GPT-3.5 Turbo, which is tailored to work with the Chat Completions API.
- Generates concise summaries of longer text, such as documentation and reports.
- Generates content for various use cases and writing projects, such as emails and code.
The GPT-3.5 Turbo models are upgraded versions of GPT 3.5, with more fine-tuned language comprehension and next-generation capabilities. Users can access three model variants through the GPT-3.5 Turbo API:
- Gpt-3.5-turbo-instruct is an instruction model that provides terser and more relevant responses. It supports a 4,096-token context window.
- Gpt-3.5-turbo-1106 has a 16,385-token context window for faster and more efficient processing.
- Gpt-3.5-turbo-0125 supports a 16,385-token context window with improvements that include higher accuracy at responding in requested formats and a fix for a bug that caused a text encoding issue for non-English language function calls.
GPT-3 vs. GPT-3.5
In June 2020, OpenAI released GPT-3. Following GPT-1 and GPT-2, the vendor's previous iterations of the generative pre-trained transformers, GPT-3 became the largest and most advanced language model. The large language model works by training itself on large volumes of internet data to understand text input and generate text content in various forms.
In November 2022, OpenAI released its ChatGPT chatbot, powered by the underlying GPT-3.5 model, an updated iteration of GPT-3. GPT-3.5 has improved language comprehension and text creation and reduced model bias. While sometimes still referred to as GPT-3, it is GPT-3.5 that underlies the free version of ChatGPT today.
GPT-4
OpenAI designed GPT-4 to be more reliable, creative and capable of handling nuanced instructions than its predecessors. GPT-4's extended capabilities include the following:
- Multimodality. GPT-3 is unimodal, so it can only process and generate text. GPT-4 can process both text and images.
- Larger context windows. Context windows refer to the number of tokens a model will accept as an input. The larger the context size, the more prompts you can fit into your window. GPT-3.5 has an input context window of 16,000 and an output context window of 4,000. GPT-4 has a context window of up to 128,000 for input and 4,000 for output. GPT-4's larger window size enables use cases such as long-form content creation, extended conversations, and document search and analysis.
- Capabilities. GPT-3.5 was trained on 175 billion parameters, while GPT-4 was trained on a parameter close to 1 trillion. This provides GPT-4 versions with more advanced contextual awareness and reasoning capabilities than their GPT-3.5 counterparts.
- Broader general knowledge. GPT-4 versions are trained on a larger, more diverse data set that lets them process more complex requests, such as composing songs, writing screenplays or learning a user's writing style.
- User experience. GPT-4 offers a more humanlike, seamless experience with improved context retention and response depth. However, GPT-4 is slower than GPT-3.5 due to the increased computational demands associated with its 1 trillion parameters.
- Accuracy. According to OpenAI, GPT-4 demonstrates human-level performance on various professional and academic benchmarks. Its factual accuracy is 40% higher than that of GPT-3.5. It is also 82% less likely to generate unsafe content than GPT-3.5. GPT-3.5 is only trained on content up to September 2021, limiting its accuracy on queries related to more recent events. GPT-4, however, can browse the internet and is trained on data through April 2023 or December 2023, depending on the model version.
Recent research indicated that the performance and behavior of both GPT-3.5 and GPT-4 can vary greatly over time. For example, one model might surpass the other in a specific construct, such as accuracy, during particular periods.
Availability and pricing
GPT-3.5 is free, while its Turbo versions charge a fee.
GPT-3.5
The following table details GPT-3.5 Turbo API costs.
| GPT-3.5 Turbo API pricing | ||
| Model | Input | Output |
| Gpt-3.5-turbo-1106 | $1.00 per 1 million tokens | $2.00 per 1 million tokens |
| Gpt-3.5-turbo-0125 | $0.50 per 1 million tokens | $1.50 per 1 million tokens |
| Gpt-3.5-turbo-instruct | $1.50 per 1 million tokens | $2.00 per 1 million tokens |
GPT-4
GPT-4 is free. GPT-4 Plus and GPT-4 Pro cost $20 and $200 per month, respectively. See ChatGPT pricing for details.
The following table details GPT-4 API costs.
| GPT-4 API pricing | ||
| Model | Input | Output |
| 128,000-token context lengths (gpt-4-turbo) | $0.01 per 1,000 prompt tokens | $0.03 per 1,000 sampled tokens |
| 8,000-token context lengths (gpt-4 and gpt-4-0314) | $0.03 per 1,000 prompt tokens | $0.06 per 1,000 sampled tokens |
| 32,000-token context lengths (gpt-4-32k and gpt-4-32k-0314) | $0.06 per 1,000 prompt tokens | $0.12 per 1,000 sampled tokens |
Introduction to GPT-4 Turbo
In November 2023, OpenAI debuted GPT-4 Turbo, along with a GPT-4 Turbo with Vision model, with a larger context window and significantly cheaper pricing. Its 128,000-token context window -- equivalent to sending approximately 300 pages of text in a single prompt -- offers enhanced accuracy, speed and versatility. It's also three times cheaper for input tokens and two times more affordable for output tokens than GPT-4, which has a maximum of 4,096 output tokens.
| GPT-4 Turbo API pricing | ||
| Model | Input | Output |
| GPT-4 Turbo | $10 per 1 million prompt tokens | $30 per 1 million sampled tokens |
| GPT-4 Turbo with Vision | $10 per 1 million prompt tokens | $30 per 1 million sampled tokens |
Rate limits on how often the model can be used within a specified period of time are available in the rate limits guide.
Update and future
On May 13, 2024, OpenAI released the more powerful, cost-effective and faster GPT-4o. This was followed by the release of GPT-4o mini, a scaled-back and cheaper version of GPT-4o. A growing number of clues indicate that OpenAI will release a GPT-5.0 version sometime in 2025.
OpenAI's original goal was to produce a large language model (LLM) with artificial general intelligence that passes the Turing test. Researchers claim generative models have long passed the human intelligence threshold. Indeed, OpenAI CEO Sam Altman aspires to create software bots with artificial superintelligence that outperform humans.
Ethical considerations
GPT-3.5 and GPT-4 raise significant ethical considerations. These powerful LLMs can generate convincing but potentially false or harmful content, perpetuating biases present in their training data. Concerns include the following:
- Spread of misinformation.
- Automation of harmful tasks.
- Potential for job displacement.
- Erosion of human creativity.
Responsible development and deployment are, therefore, crucial. They require ongoing research into mitigating biases, detecting and addressing harmful outputs, and developing transparent and accountable systems.
Editor's note: This article was updated in February 2025 to provide additional information on GPT 3.5 Turbo models, more details on GPT-4 capabilities and new pricing.
Leah Zitter, Ph.D., is a seasoned writer and researcher on generative AI, drawing on over a decade of experience in emerging technologies to deliver insights on innovation, applications and industry trends.
Will Kelly, a freelance writer and content strategist, previously contributed to this article.
