GPT-5 Complete Review: OpenAI's Latest AI Breakthrough 2025
Glyphiq
GPT-5 Complete Review: OpenAI’s Latest AI Breakthrough 2025
So I’ve been messing around with GPT-5 for the past couple weeks. Gotta say, I went in pretty cynical - we’ve all been burned by AI hype before, right? “Revolutionary this, breakthrough that.”
But damn. This one’s different.
Got early access through work (perks of being in tech, I guess), and honestly? First hour of testing had me texting my developer friends like “dude, you need to see this.”
Released August 7th after months of Sam Altman’s cryptic tweets. Was starting to think it was vaporware, but turns out they were actually building something legit behind the scenes.
The Waiting Game Finally Ends
Remember all those “GPT-5 coming soon” tweets from Sam Altman? Yeah, we’ve been hearing that since early 2025. I was starting to think it was becoming the AI equivalent of “Half-Life 3 confirmed.”
But turns out they were actually cooking something substantial behind the scenes. And honestly? The delay makes sense now that I’ve seen what they built.
Here’s what surprised me most: they didn’t just make GPT-4 faster or add a few bells and whistles. They basically rethought how the whole thing works. No more jumping between different AI tools for different tasks - this thing handles pretty much everything you throw at it.
Okay, The Numbers Are Actually Insane
Look, I hate benchmark porn as much as the next person. But I ran some tests myself because I’m skeptical like that.
Math stuff: Got 94.6% on AIME 2025. For context, I can barely solve these problems with a calculator and Wikipedia open. Asked it to walk me through one of the geometry problems that stumped me in college - explained it like I was five, then showed three different solution approaches. Kinda embarrassing tbh.
Code reviews: This is where I got excited. 74.9% on SWE-bench Verified (that’s actual GitHub issues, not leetcode bullshit). I fed it a gnarly bug from our production codebase that took our team two days to track down. Found it in like 10 minutes. Then suggested a refactor that was… actually pretty good?
Also hit 88% on Aider Polyglot. Means it doesn’t just regurgitate Python tutorials - I tested it on some weird Rust edge cases and legacy JavaScript from hell. Handled both like a champ.
Image processing: 84.2% on MMMU. Threw my chicken-scratch whiteboard photos at it (you know, those “temporary” diagrams that become permanent documentation). Actually made sense of my terrible arrows and abbreviated notes. Though it thought my drawing of a database was a sandwich, so… progress?
Healthcare benchmark was 46.2% which sounds low but honestly, that’s terrifying enough. I’m not letting an AI diagnose anything, thanks.
The “Thinking” Thing Is Actually Cool
This was the feature I was most skeptical about. “Minimal reasoning” sounds like marketing speak, right? But after playing with it… it’s genuinely different.
When you enable the thinking mode, you can actually see it working through problems step by step. Not just generating text that looks like reasoning - actual logical progression. Accuracy jumps from 77.8% to 85.7% when it’s “thinking,” and you can feel the difference in the responses.
I tested it on some logic puzzles I knew the answers to, and watching it work through the problem was pretty fascinating. Still feels weird to say an AI is “thinking,” but… that’s kind of what it looks like?
Tool Usage That Actually Works
Remember how previous models would confidently call the wrong API or hallucinate function parameters? GPT-5 hits 96.7% accuracy on tool calling tasks. I’ve been using it to automate some of my workflows, and it’s the first AI that consistently gets the tool chaining right.
Set it up to pull data from one API, process it, and push to another system - works like a charm. No more babysitting the process or fixing broken function calls.
Code Generation Gets Serious
As a developer, this is where GPT-5 really shines. I asked it to build me a simple inventory management app, gave it maybe three sentences of description, and got back a fully functional React app with proper state management, error handling, and even some decent CSS.
Not just “hello world” stuff - actual applications that you could use. Still had to tweak a few things (old habits die hard), but the base was solid. Way beyond anything I’ve seen from previous models.
Three Flavors to Choose From
OpenAI released three versions:
- GPT-5 Full: The whole enchilada
- GPT-5 Mini: Faster, cheaper, still pretty capable
- GPT-5 Nano: For when you need something lightweight
I’ve mainly been testing the full version, but Mini is surprisingly good for most tasks. Nano… well, it’s fine for simple stuff, but you can tell it’s been stripped down.
Knowledge cutoff is September 2024 for the full model, May 2024 for the smaller ones. Not super recent, but better than GPT-4’s training data.
Context Window That Swallows Novels
272,000 token input limit. That’s roughly a short novel’s worth of text. I threw my entire project documentation at it (about 200 pages) and it actually understood the whole thing. No more “sorry, your input is too long” errors.
Output limit is 128,000 tokens, which includes the invisible reasoning tokens. More than enough for most use cases, though I did hit the limit once when asking for a very detailed technical specification.
Real-World Testing Results
I’ve been using GPT-5 for actual work over the past two weeks. Here’s what I found:
Business stuff: Great for analyzing reports, writing proposals, and handling complex workflows. I had it process a 50-page market research document and extract key insights - saved me probably 4 hours of reading.
Education: Helped me understand some complex machine learning concepts I’d been struggling with. The step-by-step explanations are genuinely helpful, not just regurgitated textbook content.
Creative work: Asked it to help brainstorm some article ideas. Got back stuff that was actually creative, not the usual generic suggestions.
Where It Still Falls Short
Let’s be real - it’s not perfect. Long documents with mixed text and images still trip it up sometimes. I had a PDF with charts and technical diagrams, and while it got the gist, it missed some important details in the visual elements.
Also, like all AI models, it can be confidently wrong. I caught it making up a few “facts” about obscure technical topics. Always double-check anything important.
And if you want the full experience, you need serious computational resources. The free tier is pretty limited.
Pricing Reality Check
- Free: You get a taste, but it’s quite limited
- Plus ($20/month): Decent access for most users
- Pro ($200/month): For heavy users (which I definitely became)
- Enterprise: Custom pricing, all the bells and whistles
I upgraded to Pro after about a week of testing. Worth it if you’re using AI regularly for work.
What This Actually Means
Look, I’ve seen a lot of “revolutionary” AI releases that turned out to be incremental improvements with good marketing. GPT-5 feels different. Not because it’s AGI or anything dramatic like that, but because it’s the first AI that consistently feels like working with a competent collaborator rather than a sophisticated autocomplete.
The reasoning capability, the tool integration that actually works, the massive context window - it adds up to something qualitatively different from what came before.
Will it replace developers, writers, analysts? Probably not entirely. But it’s definitely going to change how we work. I’m already finding myself approaching problems differently, knowing I have this kind of AI assistance available.
So Is It Actually Worth It?
Two weeks in, and I’m still using it daily. That says something, right? Usually by now I’d have gotten bored and moved on to the next shiny thing.
Cost is real though. Free tier is basically a demo, Plus ($20) gets you started, but Pro ($200) is where the magic happens. I justified it as a work expense, but that’s not pocket change.
Perfect? Hell no. Still hallucinates occasionally (caught it making up Python libraries last week). Still needs babysitting on important stuff. And sometimes it gets confidently wrong about things I know better.
But here’s the thing - it’s the first AI that feels less like a tool and more like… having a really smart intern? One who never sleeps, never gets moody, and occasionally comes up with ideas I wouldn’t have thought of.
My workflow’s already changed. Instead of googling for solutions, I just ask it to walk me through problems. Instead of staring at blank pages, I bounce ideas off it first. It’s become part of how I think through stuff.
The hype machine will probably claim this changes everything tomorrow. It doesn’t. But it does change enough that I’m not going back to working without it.
Worth checking out if you do anything complex with computers. Just remember it’s a tool, not magic. A really good tool, but still a tool.
Anyway, gotta run - found some new edge cases to break…