Introduction
I've spent the past year testing every major AI model I could get my hands on, and in the space of 12 months, a lot has changed. The models have become noticeably more refined, more reliable, and the agentic tooling has matured significantly.
As we reach the end of 2025, I wanted to put together a roundup of where we actually are: which models are the best, where each of them shines, and what my day-to-day workflow looks like. This covers Gemini 3, ChatGPT 5.2, Claude 4.5 Opus, and Grok 4.1.
The short version: the top models are broadly excellent, but they're optimised for different things. My goal here is to help you see where each model shines, and which subscriptions might actually be worth it for your use case.
Let's get into it.
TL;DR (My Current Defaults)
| Model | Best At | Where It Falls Short | When I Reach For It |
|---|---|---|---|
| Gemini 3 Pro | Multimodal understanding, education, visualisation | Less steerable; can drift | Explaining concepts, product strategy, UI ideation |
| Gemini 3 Flash | Speed + strong reasoning | Not always as deep as Pro | Quick answers, lightweight coding + analysis |
| GPT-5.2 Pro | Deep reasoning, research, complex planning | Slow (but often worth it) | High-stakes thinking, architecture decisions |
| GPT-5.2 Thinking | Professional reasoning, research synthesis | Can be slow; sometimes too specific vs generalised | Research, careful instruction-following |
| GPT-5.2 Codex | Agentic coding, bug finding, edge cases | More narrowly focused | Sanity checks, catching bugs others miss |
| Claude Opus 4.5 | Agentic coding, implementation, terminal workflows | Multimodal/general agentic less strong than others | Shipping features, refactors, bug hunts |
| Grok 4.1 | Real-time context, X-native utility | SOTA window can be short | Breaking news, fact-checking threads |
Gemini 3: The Multi-Modal Generalist
For general life use (learning, thinking, advice, multimodal tasks), Gemini 3 is hard to beat, especially when you want explanations grounded in timeless knowledge rather than breaking news.
What stands out is the breadth:
- One of the strongest at image understanding and multimodal reasoning
- A convincing "world understanding" feel, especially for explanations that need to be factually grounded
- Unusually good at generating supporting artefacts (visualisations, interactive demos) that make explanations stick
That last point matters more than people think. When you ask a model to explain a physics concept or a systems design idea, the ability to generate a clean visual companion turns "I get it intellectually" into "I actually understand it."
Pro vs Flash:
- Flash is my "quick brain", fast enough to feel conversational
- Pro is for when the quality of explanation matters and I want richer output
Where Gemini trips up:
- Steerability. It can wander from tight constraints
- Reliability under specs. For engineering tasks, it can sound right and be wrong in small ways you only notice when you run the code
Gemini is my favourite generalist. But I don't rely on it as my primary "ship this to production" model.
ChatGPT 5.2: The Research & Reasoning Workhorse
GPT-5.2 feels like it's been trained to actually complete work, especially when tools are involved, and to hold onto the messy structure of a task without collapsing it into something simpler.
The Tiers:
- Instant: Quick sanity checks, obvious facts, lightweight drafting
- Thinking: The professional default. Strong at multi-step work, particularly when tasks are ambiguous or partially specified. Also excellent at getting up-to-date answers when live information matters
- Pro: The "slow genius" tier. What I use when I need depth, thoroughness, and getting to the actual point rather than a plausible answer
- Codex: The agentic coding specialist. One of the best at bug finding and catching edge cases. I use it as a sanity check when something feels off
If you've ever had a model give you a response that's "fine", but you can feel it avoided the hard part, Pro is the antidote. It's slow, and I don't use it casually, but for planning something significant it's the closest thing to a genuinely useful thought partner I've seen.
For Coding:
- GPT-5.2 Pro excels at greenfield planning, architecture, and trade-off thinking
- In Codex-style workflows, it's an extremely capable implementation partner when you're prescriptive
Claude 4.5 Opus: The Engineer
Right now, if your primary goal is to build software, Claude Opus 4.5 is the best default.
Not because it's the "smartest at everything", but because it's the best at the full loop: understand the task, write the code, handle edge cases, fix the tests, refactor without breaking things, and keep going for longer than you'd expect.
Paired with Claude Code or Cursor, the experience is genuinely agentic. At minimum it behaves like a junior engineer who can grind through work, but often it's far more capable than that. When you learn to use it well, the productivity gains can exceed what you'd get from almost any human engineer. This is one of those models that feels like it's crossed a threshold: reliable and powerful enough that many in the industry are starting to treat it as a genuine part of their workflow rather than an experiment.
Why I trust it for implementation:
- It stays on track. When you give it a spec, it's less likely to drift into a different spec
- The bug-finding instinct is excellent. It catches the boring-but-deadly issues that make code unreliable
Computer Use & Tools:
Claude's ability to interact with the terminal and browser is impressive. The tool ecosystem (operating in an agentic way, interacting with browser environments, following a UI and iterating) sounds gimmicky until you've used it for real debugging or QA-style work.
Where Claude loses:
If I'm being honest, Claude doesn't consistently beat GPT-5.2 Pro for high-level architecture with subtle trade-offs, long-range planning with lots of constraints, or deep reasoning where you want the model to sit with a problem. For general agentic tasks outside of coding, GPT has the edge. And for multimodal understanding and conceptual explanations, Gemini is still stronger.
My split is simple:
- Claude Opus 4.5 ships the thing
- GPT-5.2 Pro decides what the thing should be (and why)
Grok 4.1: The Real-Time Truth Seeker
Grok's biggest advantage isn't always raw model power. It's distribution and workflow.
If you spend any time on X, the Grok integration is genuinely useful: you see a claim, tap a button, and get context, counterpoints, and sometimes a quick credibility check. That frictionless "context expansion" is the killer feature.
Grok releases tend to be impressive, but the "state-of-the-art window" can be short because the frontier is so competitive. Still, Grok 4.1 is worth having because it's optimised for real-time information, breaking news context, and the messy social layer of the internet.
The Meta Takeaway: We've Entered the Portfolio Era
At a high level:
- Google (Gemini 3) is optimising for breadth: world understanding, multimodality, visual intelligence
- OpenAI (GPT-5.2) is optimising for agentic productivity: tool use, research workflows, deep reasoning
- Anthropic (Claude Opus 4.5) is optimising for software engineering: agentic coding, implementation quality
- xAI (Grok 4.1) is optimising for real-time context: the live internet layer
At this scale, you can't maximise everything equally. You pick your priorities, and the products start to feel different.
My Current Stack
Here's the pipeline that consistently gives me the best results:
- Big planning / architecture: GPT-5.2 Pro
- Implementation / refactors: Claude Opus 4.5
- Code review / bug checking: GPT-5.2 Codex
- UI taste + visual output + multimodal input: Gemini 3 Pro
- Quick everyday questions: Gemini 3 Flash
- Breaking news / internet context: Grok 4.1
If you only want one or two subscriptions:
For most people, ChatGPT Plus is the best single subscription right now. The product ecosystem is the most complete: you get near-unlimited access to Instant, generous limits on the Thinking model, and solid access to Codex for coding workflows.
That said, specific needs point elsewhere:
- Software engineers: Claude (Pro or Max) is the better choice if coding is your primary use case
- Design, education, learning, visualisation: Google AI Pro offers excellent multimodal capabilities and a versatile generalist experience
- News, publishing, real-time context: SuperGrok (or X Premium+ if you're already on the platform)
Google AI Pro is genuinely strong for broad, everyday use—and the underlying Gemini model can beat ChatGPT in many ways. But ChatGPT's product ecosystem feels more complete and polished as a single subscription.
Final Thoughts
The most interesting thing about the end of 2025 isn't "which model won."
It's that the top models are now good enough that specialisation actually matters. We're in the portfolio era. Each lab is optimising for something different, and the products genuinely feel different as a result.
If you use them like interchangeable chatbots, you'll get interchangeable results. If you treat them like a toolkit—each one doing what it's best at—you'll notice a real difference in what you can get done.