GPT-4.5 vs GPT-4o: Comparing OpenAI’s Latest AI Models
A deep look at two of OpenAI’s most powerful models.
OpenAI’s GPT-4.5 and GPT-4o are two advanced generative AI models that build on the success of GPT-4. Although they share a common lineage, these models have distinct focuses and strengths. GPT-4o (with “o” for “omni”) was introduced in mid-2024 as a multimodal model integrating text, vision, and audio capabilities. GPT-4.5 followed in early 2025, just a few weeks ago, as a scaled-up language model aimed at greater knowledge and conversational intelligence.
Below I compare their key features, performance in tasks like writing and coding, user-reported pros and cons, and how they’re being received in real-world use.
Performance in Writing, Coding, and Reasoning
When it comes to language and writing tasks, GPT-4.5 has a clear edge in creativity and nuance. OpenAI describes GPT-4.5 as having a more “thoughtful personality” that excels at creative writing and natural conversation.
In one test carried out by techradar, GPT-4.5’s answers often feel more human-like and context-aware. For example, one side-by-side test found both models answered a movie trivia question correctly, but GPT-4.5 gave a smooth, explanatory response in plain paragraphs, whereas GPT-4o’s answer was formatted as an odd list – technically correct but less natural to real.
This reflects GPT-4.5’s higher emotional intelligence and ability to pick up subtle cues. In fact, early users report GPT-4.5 is better at sensing tone or unstated preferences in a prompt, like giving a simpler recipe when someone says they’re “bored of pasta.” It tends to “recognize the unstated preferences” a bit more, though the difference can be very subtle. By contrast, GPT-4o’s writing is described as efficient, accurate, and practical but more straightforward in style. In everyday scenarios, GPT-4o already produces solid results – casual users might not notice a big gap without a direct comparison.
For coding and reasoning tasks, both models are capable, but GPT-4.5’s expanded training gives it an advantage on complex problems. Benchmark tests indicate GPT-4.5 outperforms GPT-4o across domains like science Q&A, math, and software engineering challenges. For instance, GPT-4.5 scored 71.4% on a scientific knowledge quiz versus GPT-4o’s 53.6%, and it solved more real-world coding problems (about 33% vs 23% in one software engineering benchmark). These improvements mean GPT-4.5 is more reliable for difficult programming tasks or multi-step reasoning. However, GPT-4.5 is not a specialized “logic” model – OpenAI notes it doesn’t outperform their dedicated reasoning-focused models (the “o1” series) on heavy math or logic puzzles.
In other words, GPT-4.5 closes much of the gap and hallucinates far less (making fewer factual errors) than GPT-4o, but on extremely complex logic, it can still struggle. GPT-4o itself was roughly on par with the older GPT-4 in pure text tasks, so it’s strong, just not as “deep” on knowledge and reasoning as GPT-4.5.
In terms of efficiency, GPT-4o was designed for speed and lower cost, especially in multimodal settings. It can respond to spoken queries in a fraction of a second (averaging ~320ms, approaching human conversation speed). This low latency makes GPT-4o feel very responsive, enabling use cases like real-time voice translation. In fact, OpenAI demonstrated that GPT-4o’s fast speech processing could translate conversations on the fly. GPT-4o is also optimized to be cheaper to run, roughly 50% less costly in the API than the original GPT-4. GPT-4.5, on the other hand, is a much larger model pushing the limits of compute. It currently has significant computational cost. Responses from GPT-4.5 may be a bit slower due to the model’s size (users have noted slightly longer waits compared to GPT-4o), and OpenAI has imposed message caps and a gradual rollout because of the heavy GPU requirements.
Essentially, GPT-4.5 trades some efficiency for higher proficiency. Its context window is huge (able to analyze long documents up to ~128k tokens, similar to GPT-4o), which is useful for extended dialogues or file analysis. But the practical effect is that GPT-4o feels more nimble, while GPT-4.5 feels more knowledgeable.
Pros and Cons of Each Model
Based on expert analyses and user experiences, each model comes with advantages and drawbacks:
GPT-4.5 Pros:
Broader Knowledge & Accuracy: Trained on more recent data (through late 2024), GPT-4.5 can handle up-to-date queries better and gives more factual answers with fewer mistakes. Users see significantly improved accuracy on knowledge questions and far lower tendency to “hallucinate” incorrect facts.
Nuanced, Creative Responses: It demonstrates higher emotional intelligence and creativity. GPT-4.5 often produces more natural-sounding replies, picks up subtle intent, and even infuses a bit of personality or “EQ” into answers. This makes it well-suited for creative writing, storytelling, or sensitive advice where tone matters.
Strong Performance Across Tasks: In evaluations, GPT-4.5 consistently outperforms GPT-4o on complex tasks – from coding and scientific reasoning to multilingual understanding. It’s viewed as OpenAI’s “most knowledgeable” model so far, often able to integrate ideas and solve problems that GPT-4o might struggle with.
GPT-4.5 Cons:
High Cost & Limited Access: The model’s API usage is more expensive per token than GPT-4o. This steep cost puts it out of reach for many casual users and small businesses, a point of frustration for those eager to try GPT-4.5.
Not Fully Multimodal (Yet): Unlike GPT-4o, GPT-4.5 doesn’t natively handle audio input/output. It can analyze text and images, but features like built-in voice conversation or real-time video understanding are not supported in this preview. For users, this means GPT-4.5 can’t directly talk or listen; it’s focused on text-based interaction for now.
Incremental Upgrade Feel: Some early adopters note that GPT-4.5, while better, isn’t a dramatic leap in everyday use. Its improvements can be “very subtle” unless you have specific demanding tasks. For general Q&A or simple help, GPT-4o already performs well, so the difference with GPT-4.5 might not justify the cost for everyone. In short, it’s an evolutionary step rather than a revolutionary one, pending further refinement.
GPT-4o Pros:
Rich Multimodal Abilities: GPT-4o’s hallmark is seamlessly handling text, images, and speech together. It can interpret a picture, carry on a spoken dialogue, and even respond with synthesized audio in one model. This “all-in-one” capability unlocks interactive uses like voice assistants that truly understand tone or image-based conversations.
Fast and Efficient: A major advantage of GPT-4o is speed. It was engineered for real-time responsiveness, with latency on speech queries comparable to human reaction time. This makes conversations feel fluid. It’s also far more cost-effective to use. In the API, GPT-4o is priced at a fraction of GPT-4.5’s cost.
Practical and Reliable: GPT-4o is often described as a solid workhorse for everyday tasks. It follows instructions well and produces accurate, concise answers in most common scenarios. Its outputs tend to be direct and to-the-point, which can be a benefit for productivity.
GPT-4o Cons:
Limited Knowledge Updates: GPT-4o’s training data cuts off around late 2023, so it may lack awareness of very recent events or information (without resorting to external tools). It doesn’t have the extended knowledge span that GPT-4.5 offers out-of-the-box. For users, this means GPT-4o might occasionally respond with outdated info or require workarounds (like the browsing tool) to handle current topics.
Higher Hallucination Rate: While powerful, GPT-4o is more prone to factual errors under pressure. Evaluations showed it has a significantly higher hallucination rate on tricky questions (e.g. answering confidently with incorrect facts) compared to GPT-4.5. Users have noticed that GPT-4o can sometimes go off track or misinterpret complex requests, requiring careful prompting. Its factual accuracy, though good, isn’t as robust as GPT-4.5’s in critical applications.
Less “Intuitive” Responses: In direct comparisons, GPT-4o’s answers can be a bit more formulaic or blunt. It may follow the letter of the request and produce a correct result, but without the extra finesse in phrasing or insight that GPT-4.5 might show. For example, GPT-4o might enumerate points in a list when a flowing explanation would be nicer. It also lacks the deeper emotional attunement — it won’t be as sensitive in tone or as creative in storytelling as GPT-4.5. For highly nuanced tasks (persuasive writing, delicate advice, etc.), GPT-4o’s replies, while competent, could feel somewhat flat or overly factual.
The Bottom Line
Both models have attracted substantial user feedback since their releases. GPT-4o initially wowed users with its multimodal demos – people saw it playing games, translating speech instantly, and describing images in ways previous ChatGPT versions couldn’t. OpenAI showcased scenarios like two colleagues using GPT-4o for real-time voice translation during a conversation, and GPT-4o acting as a virtual guide for a person by analyzing live camera footage and narrating the scene to assist the visually impaired.
Such use cases impressed many, and companies began exploring GPT-4o for interactive customer service bots, language learning apps, and accessibility tools. Users generally praise GPT-4o’s speed and versatility – it “feels” more responsive and interactive than earlier models. Some did report occasional quirks or errors (as any AI model will have), and a few technical users noted that GPT-4o might skip step-by-step reasoning on complex tasks, focusing more on quick answers. Overall, the reception of GPT-4o has been positive, especially because it brought advanced AI capabilities to the broader public via the affordable ChatGPT Plus plan.
The release of GPT-4.5 came with high expectations – and a bit of skepticism. Early testers generally agree that GPT-4.5 is indeed better, but the improvements can be nuanced. “You'll need to be a power user to really notice” big differences.
That said, OpenAI itself positions GPT-4.5 not as a replacement for GPT-4o but as a higher-end option for those who truly need its extra capabilities. Many organizations might continue using GPT-4o for day-to-day tasks and switch to GPT-4.5 for specialized cases.
In my personal, everyday experience, GPT-4o stays more on-task for simple activities like email replies or text proofreading, whereas GPT-4.5 can sometimes be overly creative or misinterpret prompts. For instance, when asked to comment on a short document flow and clarity, it ignored the request entirely and rewrote the whole piece instead, clearly missing the point and hallucinating.
In summary, GPT-4o and GPT-4.5 serve different niches in OpenAI’s lineup. GPT-4o is all about making AI more accessible and interactive – it’s the model that “can do everything” (text, images, speech) reasonably well and quickly, which is fantastic for broad consumer and business use. GPT-4.5 is focused on pushing the quality envelope – it’s the model you turn to for the most challenging queries, where you need that extra level of understanding, creativity, or factual accuracy (and you’re willing to pay a premium for it).
Keep a lookout for the next edition of AI Uncovered!
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