OpenAI’s o3 and o4-mini: Your New AI Allies for Coding and Visual Analysis
OpenAI has just launched two groundbreaking models, o3 and o4-mini, that are revolutionising the way we approach AI for coding and visual analysis. As someone who’s tested these extensively, I’m excited to share what these new tools can actually do for you.
What are OpenAI’s o3 and o4-mini models?
Let me break it down for you…
o3 is OpenAI’s advanced model designed for complex technical tasks. Think of it as your brilliant tech friend who excels at coding, visual analysis, and reasoning.
o4-mini is the smaller, more efficient version that packs incredible mathematical and coding capabilities into a more affordable package.
Both integrate seamlessly with the tools you already use, making them practical additions to your tech stack rather than just flashy new toys.
What tasks can o3 handle effectively?
o3 absolutely shines when dealing with:
- Complex programming challenges – it scored 69.1% on SWE-bench
- Visual analysis – it can examine images from multiple angles
- Multi-step reasoning problems
- Business strategy development
- Web browsing assistance
I recently tested o3 on a tricky Python debugging issue that had me stumped for days. It not only identified the root cause but suggested three alternative approaches I hadn’t considered.
If you’re looking to enhance your ethical AI practices, these models offer significant transparency in their reasoning processes.
What makes o4-mini special despite its smaller size?
Don’t let the “mini” fool you – this model is mighty:
- Exceptional mathematical performance (99.5% on AIME 2025 benchmark)
- Faster processing speeds
- More efficient with resources
- Higher usage limits than previous models
- Strong data science capabilities
The way o4-mini handles Python code execution is frankly impressive. I’ve watched it analyse data sets and generate visualisations in seconds that would have taken me at least 30 minutes to code manually.
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How much do these models cost to use?
Let’s talk money – always important for businesses watching the bottom line:
| Model | Input Cost | Output Cost |
|---|---|---|
| o3 | £10 per million tokens | £40 per million tokens |
| o4-mini | £1.10 per million tokens | £4.40 per million tokens |
Both models are available to ChatGPT Plus, Pro, and Team subscribers. For developers building applications, they’re accessible through OpenAI’s API with usage-based pricing.
For perspective, a typical business query might use 500-1000 tokens, making o4-mini extremely cost-effective for routine tasks.
Are these models safe to use for business applications?
Safety is non-negotiable when implementing any AI solution.
OpenAI has put both models through comprehensive testing using their Preparedness Framework. This includes:
- Rigorous safety evaluations
- Stress testing across various scenarios
- Content filtering capabilities
- Regular monitoring and updates
While no AI is perfect, these models represent some of the most ethically developed options currently available.
What is Codex CLI and how does it work with these models?
Codex CLI is OpenAI’s terminal-based tool that brings AI assistance directly to your command line.
It runs locally on your machine and connects to OpenAI’s models to help with:
- Generating code snippets
- Debugging problems
- Explaining complex commands
- Automating repetitive tasks
I’ve been using Codex CLI with o3 to automate my development workflow, and it’s been a game-changer for productivity. Tasks that used to take me an entire morning now take minutes.
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How do these compare to other AI models like Claude or Gemini?
Based on my testing across various models:
- o3 outperforms competitors in technical reasoning and code generation
- o4-mini offers better price-to-performance for mathematical tasks
- Visual analysis capabilities are more advanced than most alternatives
- Integration options are more flexible than Claude
The main advantage I’ve found is the balance between specialisation and versatility. Unlike some models that excel in narrow domains, these new OpenAI offerings maintain high performance across a broad range of applications.
For businesses looking to integrate AI into their workflow, this versatility means fewer tools to manage and less technical debt.
Can these models help with business strategy, not just technical tasks?
Absolutely. While technical capabilities get the headlines, I’ve found these models surprisingly adept at business strategy too:
- Market analysis and competitive research
- Financial modelling and forecasting
- Product development planning
- Customer feedback analysis
Last month, I used o3 to analyse customer survey data for a client, and it identified three sentiment patterns we’d completely missed in our manual review.
The ability to process and synthesise large volumes of information makes these models valuable for ethical business decision-making at every level.
Are OpenAI’s o3 and o4-mini worth the investment?
After extensive testing, my verdict is a strong yes – with caveats:
These models are worth it if you:
- Regularly work with code or data analysis
- Need to process visual information systematically
- Value time savings over perfect outputs
- Have the technical knowledge to verify results
They might not be worth it if you:
- Need 100% accuracy without human oversight
- Primarily work with creative rather than analytical content
- Have significant budget constraints
OpenAI’s o3 and o4-mini models represent a significant step forward in making advanced AI capabilities accessible to businesses of all sizes. Whether you’re debugging code or analysing visual data, these tools offer practical solutions that deliver real value.
Written by Hayley Brown, owner of allin1app.com, lover and obsesser of all things AI and automation and provides significant added value for readers including how to set up time saving automations using https://www.make.com/en/register?pc=hayleyallin1