GPT-4o vs GPT-4.5 vs o3 - How to find the right ChatGPT model in 2025
Introduction
In 2025, choosing the right AI model is more important than ever. OpenAI has greatly expanded its range of models - with GPT-4o, GPT-4.5, GPT-4.1, o3 and o4 Mini, you now have specialised models for a wide variety of applications. Whether you are a developer, entrepreneur or content creator, the right model will save you time and money and deliver significantly better results.
This article gives you a clear overview of all current GPT models - including strengths, weaknesses, prices and typical use cases. This will make it easy for you to decide which model is perfect for your project.
GPT-4o: The multimodal flagship
What is GPT-4o?
GPT-4o is the new flagship of OpenAI and a real all-rounder. The focus is on natural, fast interactions via different channels: Text, image and even voice. It is the model that is used as standard in ChatGPT (free and Plus) and delivers impressive performance.
Strengths & areas of application
- Multimodal customer service (text, image, voice)
- Real-time assistants with voice UI
- Product support with image analysis
- Voice-controlled user experiences
- Creative idea and briefing creation
Price & limits
The costs are USD 2.50 per 1 million input tokens and 10 USD per 1 million output tokens. The disadvantage? GPT-4o has weaknesses with deep logical chains (chain-of-thought) and reaches its limits with very long code sections.
GPT-4o Mini: Scalable AI on a small budget
What is the GPT-4o Mini suitable for?
GPT-4o Mini is the ideal solution for you if you are looking for mass and speed while keeping costs low. It is ideal for e-commerce chatbots, mobile voice assistants or simple multimodal processes with high volumes.
Typical use cases
- Chatbots for online shops with high traffic
- Voice agents for mobile apps
- Automatic image labelling
- AI-supported telephone systems (IVR)
- Internal team assistants
Price & compromises
The big advantage is the price: 0.15 USD Input and 0.60 USD output</strong per 1 million tokens. The downside: less sophisticated logic and occasionally inappropriate tone of voice, but extremely efficient in scaling projects.
GPT-4.5: Creativity without compromise
What makes GPT-4.5 special?
If you value emotional depth, original language and creative ideas, GPT-4.5 is your model of choice. It has been specially developed for high-quality content - ideal for marketing texts, branding, storytelling or personalised communication with sensitivity.
Strengths & use cases
- Texts with an individual brand voice
- Storytelling for content marketing or social media
- AI ghostwriting for books, speeches or newsletters
- Creative brainstorming and campaign brainstorming
- Dialogue simulation with personalised tone of voice
Price model & comparison
The costs: 2 USD input and 8 USD output per 1 million tokens. This puts GPT-4.5 between GPT-4o and o3, both in terms of price and performance. It is not quite as fast as GPT-4o Mini, but much more expressive. Ideal for content with soul.
o3: The model for deep logic & complex analyses
Why choose o3?
o3 is the undisputed champion when it comes to logic, technical depth and analysis. It was developed for specialist areas such as research, development, finance or law - wherever precise thinking counts. If you work with proofs, calculations or complex code, o3 is your best friend.
Areas of application at a glance
- Technical research & argumentation
- Refactoring and analysing large code bases
- Financial modelling and risk assessment
- Explanation of scientific diagrams
- Legal argumentation and expert opinions
Price-performance factor
Quality has its price: 10 USD input</strong and 40 USD output</strong per 1 million tokens. In addition, o3 is slower than the other models - which can be a disadvantage for longer conversations. But for complex tasks, it is worth every cent.
o4 Mini: The smart choice for start-ups & SMEs
What can o4 Mini do?
o4 Mini is the perfect solution for you if you want to achieve a lot with a limited budget. The model scores with its fast responses, strong multilingualism and RAG (Retrieval Augmented Generation) support. It is particularly suitable for internal tools, automation and international communication.
Typical fields of application
- Multilingual chatbots for knowledge databases
- Automated creation of product descriptions
- Invoice verification in large quantities
- Fast lead generation & sales preparation
- RAG-based assistants (e.g. for FAQs or internal processes)
Cost structure & weaknesses
The o4 Mini is priced at 1.10 USD Input and 4.40 USD Output per 1 million tokens - in other words, very budget-friendly. However, it is less powerful than GPT-4o for complex logical tasks or image processing. However, it is perfectly adequate for many medium-sized scenarios.
GPT-4.1: The new all-rounder for complex tasks
What is GPT-4.1?
GPT-4.1 is OpenAI's latest flagship for data-intensive tasks. It combines strong programming capabilities with a huge context capacity of up to 1 million tokens - ideal for companies that need to analyse large documents or process a lot of information simultaneously.
Strengths and application examples
- Analysing large company or contract documents
- Preparation of comprehensive project proposals and investor memos
- Summaries of meeting transcripts
- Customer satisfaction analyses based on feedback
Prices & Valuation
With 2 USD input and 8 USD Output per 1 million tokens, GPT-4.1 is comparable to GPT-4.5, but it offers significantly more "computing space" for complex tasks. If speed is more important to you, you should still consider GPT-4o - but for in-depth analyses, 4.1 is unbeatable.
Price table at a glance
Here you will find a compact price overview of the latest GPT models from OpenAI:
| Model | Input (per 1 million tokens) | Output (per 1 million tokens) | Ideal for |
|---|---|---|---|
| GPT-4o | $2.50 | $10.00 | Multimodal real-time interaction |
| GPT-4o-mini | $0.15 | $0.60 | Scalable chatbots & voice UX |
| GPT-4.5-preview | $75.00 | $150.00 | Creative content & copywriting |
| GPT-4.1 | $2.00 | $8.00 | Document & data analysis |
| o3 | $10.00 | $40.00 | Technology, research, complex logic |
| o4 Mini | $1.10 | $4.40 | SME automation & RAG workflows |
This table will help you choose the best model based on your budget and use case. In the next section, I will show you how you can make the right decision based on use case, industry and price.
Decision matrix: Which model suits which need?
According to application
| Use Case | Recommended model |
|---|---|
| Customer support (text, image, language) | GPT-4o |
| Scalable e-commerce chatbot | GPT-4o Mini |
| Brand communication & advertising copy | GPT-4.5 |
| Legal and technical analyses | o3 |
| Contract review, summarise meetings | GPT-4.1 |
| Product descriptions & multilingual bots | o4 Mini |
By industry
- Marketing & Media: GPT-4.5, GPT-4o
- Technology & IT: o3, GPT-4.1
- Startups & SMEs: o4 Mini, GPT-4o Mini
- Education & Research: o3, GPT-4.1
- E-Commerce: GPT-4o Mini, GPT-4o
By budget
- Very small budget: GPT-4o Mini, o4 Mini
- Medium budget: GPT-4.5, GPT-4.1
- Higher budget & in-depth analysis: o3
Multimodal vs Reasoning vs Creativity: Which model type suits you?
Multimodal models: When you work with image, text and language
Multimodal models such as GPT-4o (and Mini) offer you the greatest scope for natural, dialogue-oriented applications. They are ideal for interactive products, visual recognition and voice-activated systems. If you work in UX, support or communication, multimodality is key.
Reasoning models: For logical depth & technical precision
o3 and GPT-4.1 are suitable for you if your use case requires complex analyses, data-driven thinking or scientific accuracy. These models excel in research, programming, law and finance, i.e. wherever logical chains and depth of context are required.
Creative models: When tone, idea and emotion count
GPT-4.5 is your partner for brand communication, storytelling and content that stands out. Its strengths lie in the language itself: original, flexible, customisable. For copywriters, marketing teams and creative professionals, there is currently no better model.
Common mistakes when selecting the wrong GPT model
1. do not adapt the model to the use case
A common mistake is to simply choose "the best" model without considering the specific use case. For example, if you are setting up a simple FAQ chatbot, o3 is completely oversized and expensive. GPT-4o Mini or o4 Mini would be better here.
2. paying too much for simple tasks
The more complex the model, the higher the token costs. If you use GPT-4.5 or o3 for simple tasks such as product descriptions or customer service, you are paying unnecessarily high costs. Pay attention to efficiency, especially for high-volume projects.
3. select slow models for fast interaction
Models such as o3 or GPT-4.1 are excellent for deep context, but slower in terms of response time. If speed is crucial (e.g. for live chats), you should opt for GPT-4o or Mini models.
4. confuse vision and language
Not every model can handle images or speech. For multimodal requirements, you absolutely need GPT-4o or GPT-4o Mini. A classic text model such as o3 would be overwhelmed or even incompatible.
Integration tips for developers
Efficiently organising API usage
OpenAI offers you full control via the API. When implementing, make sure you keep an eye on token costs and use targeted prompts wherever possible. Also use system-prompts to stabilise the output.
Dynamic model switching
A smart approach is to dynamically select the appropriate model depending on the enquiry. Example: GPT-4.5 for creative tasks, o3 for complex analyses and GPT-4o Mini for simple questions. This allows you to optimise costs and performance.
Prompt chains and tools
Especially for more complex tasks, it is worth chained promptsi.e. multi-level queries with intermediate results. Tools such as LangChain or semantic caches also help you to get the right output from your model.
Error handling and fallbacks
Make sure your system can handle timeouts or unexpected behaviour, especially with high latency models like o3. Fallback to a faster model or static response may be useful.
Best practices for companies
Integrating the right model into the workflow
The most important success factor when using GPT models in companies is not only choosing the right model, but also cleverly integrating it into existing processes. Ask yourself: Where can GPT bring the greatest added value? Automated customer communication, internal knowledge databases or creative processes are ideal fields of application.
Utilising hybrid model strategies
Many companies now combine different models in one AI stack. For example: GPT-4o Mini for quick standard responses, GPT-4.5 for creative campaign ideas and o3 for technical documentation. This modular approach saves costs and maximises quality.
Transparency, data protection & training
Make sure your employees know how to use GPT models correctly. Clear guidelines, data protection checks and simple training help to prevent misuse and maximise potential, even without prior technical knowledge.
Define and continuously optimise KPIs
Set specific goals: Reduced processing time, higher customer loyalty, more conversions through better content. Measure the impact of your GPT utilisation using KPIs and regularly adjust the choice of model, prompts and processes.
Outlook for the future: What comes after GPT-4o, 4.5 and o3?
Growing contexts and multimodal depth
It is already clear: The future of language models lies in even larger context windows and deeper multimodal integration. This means that AI systems will be able to better process hours of conversations or complex data histories, including images, sound and document structure.
Personalised models for companies
With tools like Custom GPTs makes it easier to adapt AI models to specific brand voices or specialised content. This allows you to build your own "GPT in-house", trained on your content, data and style.
Open Source & On-Premise variants
More and more companies are asking for models that can be used locally. Whether with Mistral, LLaMA or Claude, the trend is moving towards hybrid architecturesthat combine GPTs with the company's own databases. A lot will happen here in the next 12 to 24 months.
Conclusion: staying agile pays off
The speed at which AI technology is developing is rapid. It is therefore worth remaining flexible, regularly testing new models and not relying on just one model. This will keep you technologically and economically competitive.
Conclusion: Which GPT model is right for you?
Whether you are a content creator, developer or entrepreneur, there is a suitable GPT model for every use case in 2025. If you Fast, natural communication with text, image or voice GPT-4o is unbeatable. With large amounts of data or complex analyses there is no way around o3 or GPT-4.1. And for Emotional texts and creative ideas GPT-4.5 is the measure of all things.
With models such as GPT-4o Mini or o4 Mini, you can also achieve a big impact with a small budget, especially for start-ups, internal tools or automated mass processes. Ultimately, it depends on your goals: Speed, cost, creativity or precision?
Pro Tip: You don't have to choose just one model. Integrate several GPTs into your way of working and utilise the full potential of modern AI.
FAQs - Frequently asked questions
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How do the token costs affect my monthly budget?
The costs can vary greatly depending on the model and application. Expect to pay several hundred to thousand USD per month for daily use in a medium-sized company - especially if a lot of output is generated. Use budget alerts and token counters to stay in control.
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Can I use several models at the same time?
Yes, absolutely! Many companies use a hybrid model strategy where different GPTs are used depending on the task. This allows you to maximise quality and efficiency at the same time.
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Which model is best for German-language content?
GPT-4.1 and o4 Mini offer very good multilingual support, including for German. GPT-4.5 impresses with its creative formulations, while o3 is ideal for legal or technical texts in German.
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Are there hidden costs in addition to the token prices?
Usually not. OpenAI only charges for the tokens. However, you should pay attention to network costs, latency times or possible additional costs due to long responses when using APIs.
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Which model is suitable for the legal analysis of documents?
Here, o3 is the first choice, followed by GPT-4.1. Both models offer deep logical chains, contextual understanding and are ideally suited for contracts, briefs or complex arguments.
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