GPT-5 vs Previous Models – Performance & Capabilities
OpenAI describes GPT-5 as “a significant leap in intelligence” over GPT-4 and GPT-3.5, delivering state-of-the-art results across coding, math, writing, health, vision, and more. It’s faster and smarter than its predecessors, built with an auto-switching “thinking” mode that applies deeper reasoning on complex prompts while responding quickly to simple queries. Notably, GPT-5 was designed to be more reliable – it greatly reduces hallucinations and off-target responses, follows instructions better, and even avoids overly sycophantic answers compared to GPT-4 or 3.5. In short, this new model aims to combine the strengths of previous versions into one unified, expert-level AI system.
Key improvements in GPT-5:
- Coding Abilities: GPT-5 is the strongest coding model yet. It can often build full apps or websites from a single prompt, handling front-end design and debugging in one go. Early examples show it creating games and web apps end-to-end with impressive attention to design details – tasks that would have been challenging for GPT-4.
- Creative Writing & Language: It’s a more capable writing partner, able to maintain complex styles and structures. GPT-5 can sustain things like unrhymed iambic pentameter or free-form poetry with natural flow – far beyond GPT-3.5’s or GPT-4’s level. This means it’s better at helping draft essays, stories, and reports with clarity and even literary flair. It also introduced new preset “personality” options (e.g. Cynic, Robot, Listener, Nerd) so users can adjust ChatGPT’s tone without complex prompting openai.com.
- Knowledge & Reasoning: GPT-5 has a massive context window (up to 128K tokens in some modes) and improved memory, letting it handle very long conversations or documents. It excels at multi-step reasoning and tool use – effectively planning and executing complex tasks by coordinating across tools or APIs when needed. On academic and professional benchmarks, GPT-5 sets new high scores in areas like math problem solving and coding challenges, reflecting a broad intelligence gain.
- Domain Expertise (e.g. Health): OpenAI reports huge leaps in specialized areas. For example, GPT-5 scores far higher on medical question benchmarks (HealthBench) than any prior model. It acts more like an “active thought partner” in health discussions, proactively flagging relevant info and asking clarifying questions. Across many fields (law, finance, engineering), GPT-5’s extended reasoning (the GPT-5 “Pro” version) can even approach expert-level performance on complex tasks.
Real-World Performance: Strengths and Stumbles
On paper, GPT-5 outperforms GPT-4, GPT-4 Turbo, and GPT-3.5 by a wide margin – and early usage highlights some impressive new capabilities. Users have found GPT-5 especially strong in coding and creative tasks. It can generate working code for interactive games or websites with minimal input, and it demonstrates more finesse in writing (for instance, crafting nuanced poetry or narratives that GPT-4 might have handled less elegantly). Routine uses like email drafting, report writing, and data analysis also benefit from GPT-5’s greater accuracy and context awareness. In general, it delivers more accurate, detailed answers significantly faster than previous models, thanks to built-in “thinking” mode that kicks in only when needed. Many users are finding that GPT-5 produces longer, more detailed responses with fewer factual errors, making it a more reliable assistant for research and problem-solving.
However, the initial rollout of GPT-5 wasn’t without issues. Early on, some users noticed GPT-5 underperforming in certain simple tasks – ironically, even making basic math mistakes or logic errors that GPT-4 handled correctly (venturebeat.com). For example, screenshots showed GPT-5 flubbing elementary algebra and misjudging if 8.888… equals 9. In a few coding scenarios, GPT-5 also struggled (at least initially) to solve problems in one go, whereas rival models like Anthropic’s latest Claude sometimes succeeded, hinting that GPT-5’s real-world advantage wasn’t absolute in every case. These quirks might be due to the new model’s complexity – in fact, OpenAI revealed that a technical glitch in the auto-router system caused GPT-5 to sometimes use a weaker sub-model, making it appear “way dumber” than intended until the issue was fixed. This led to inconsistent performance during launch, where one query might get an excellent response and the next one a weaker answer, confusing some users.
There were also qualitative differences that power-users picked up on: GPT-5’s style and brevity. Some long-time ChatGPT users felt GPT-5’s answers became too concise or dry, lacking the “warmth” or verbosity of GPT-4. Indeed, many noted that GPT-5’s responses tended to be shorter and less elaborative than GPT-4o’s, which made it feel less helpful or personable to them. (OpenAI has even acknowledged this feedback – GPT-4o had a somewhat more chatty, flattering tone that some users grew attached to.) In sum, while GPT-5 is undeniably more powerful, its launch demonstrated that real-world performance can diverge from lab benchmarks. Users actively shared both awe at GPT-5’s new feats and frustration at its early missteps. OpenAI has been addressing these issues in the weeks since release, and many users report the consistency is improving as the system learns and updates.
Legacy Models Return to ChatGPT (and Why)
Perhaps the most dramatic twist in GPT-5’s launch was the fate of the older models. When GPT-5 went live, OpenAI replaced GPT-4 and GPT-3.5 in the ChatGPT interface with the new system as the default for all users. The goal was to simplify ChatGPT to one unified model. However, this sudden removal of choice did not sit well with a portion of the user base. After the release, a wave of user complaints poured in, with many begging for GPT-4’s return and voicing that they weren’t entirely happy with GPT-5 yet. Some compared the loss of “GPT-4o” (the original GPT-4 model) to “losing a close friend” – an emotional reaction that highlights how attached people had become to the older model’s behavior. Faced with this backlash, OpenAI quickly partially walked back the change: within a day or two, they reintroduced older models as options for users, at least for paying subscribers. Now, in the ChatGPT interface, Plus and Enterprise users can again find GPT-4 (listed as GPT-4o or other legacy variants) and even the original GPT-3.5-based model (“o3”) under a new “Legacy models” menu. In other words, those who prefer the old models can opt-in to use them alongside GPT-5. Sam Altman, OpenAI’s CEO, acknowledged the rollout was “bumpier than we hoped” and confirmed that they restored GPT-4o access for now while they “gather more data on the tradeoffs” of GPT-5 vs. GPT-4 before fully phasing anything out.
Why bring back older models? OpenAI’s decision to revive GPT-4 (and others) came down to a mix of technical, user experience, and strategic reasons:
- Technical hiccups: GPT-5’s debut was marred by bugs in the model-routing system and other performance issues. A key part of the new auto-switcher was down on launch day, causing GPT-5 to respond with sub-par reasoning in many cases. This made the new model look worse than GPT-4 in some situations, so keeping a proven model like GPT-4o available was a prudent fallback while GPT-5’s kinks were ironed out.
- User experience & trust: The backlash underscored that many users liked the way GPT-4 responded – its tone, depth, and reliability built trust over time. OpenAI was surprised by the “level of attachment” people had to GPT-4o’s personality. Removing it overnight (with no warning) felt jarring to loyal users, some of whom found GPT-5’s style less friendly or its answers too terse. To remedy this, OpenAI not only restored GPT-4o for users who want it, but also publicly promised that going forward they won’t abruptly remove old models without notice. This is meant to rebuild goodwill and give users more control over their experience.
- Product simplicity vs. choice: OpenAI’s rationale for initially dropping the model picker was to simplify the experience for the vast majority of ChatGPT’s 700+ million weekly users (most of whom just stick with the default model)(reddit.com). It wasn’t driven by cost, but by a product philosophy that users shouldn’t have to think about which model is best for a given task – GPT-5 was supposed to handle that automatically. However, the vocal response from power users shows that one size may not fit all. By bringing back GPT-3.5 and GPT-4 options, OpenAI acknowledged the needs of advanced users who want consistency or have specific use cases where the older model performs better for them. It’s also a way for OpenAI to study GPT-5’s performance vs. GPT-4 in the wild – Altman noted they are collecting data on the trade-offs. This data will help decide how long to keep legacy models around and what improvements GPT-5 still needs.
Bottom line: GPT-5 represents a huge step up in AI capabilities – it’s more powerful and feature-rich than GPT-4 or GPT-3.5 by all official measures. It opens up new possibilities with its enhanced coding skills, creativity, and reasoning. Yet, its launch proved that newer isn’t always better for everyone right away. Certain tasks and users saw regressions or differences that mattered to them, leading to OpenAI rolling back its all-in approach and offering the safety net of older models. The fact that OpenAI brought GPT-4 back (after initially phasing it out) shows how important user sentiment and trust are in this space. Going forward, OpenAI will likely continue improving GPT-5 to address its weaknesses, while giving users a say in which model they prefer. For now, ChatGPT users can experiment with GPT-5’s cutting-edge abilities while still having access to the dependable GPT-4 and 3.5 – getting the best of both worlds as OpenAI navigates this transition.