A Practical Guide to ChatGPT, Claude, Gemini, Grok and the Best Model for Every Task

Updated September 2026

By now, most of us are using artificial intelligence in some form.

It has entered our lives remarkably quickly. We use it for research, writing, creativity, planning, organisation, coding, websites, problem-solving, social media and the heavy lifting that can make everyday work faster and considerably more manageable.

I use AI across almost every stage of my own projects, as it does the heavy lifting for my busy mind, which is usually juggling multiple projects at the same time. It helps me research and write articles, build and troubleshoot websites, explore online business ideas, create social media content, examine documents, organise information, plan projects and turn the ridiculous number of ideas floating around in my head into something I can actually work through.

But I have gradually realised one thing: Most people are still asking the wrong question about AI.

We keep asking: Which AI is the best?

ChatGPT?

Claude?

Gemini?

Grok?

Or, as I recently discovered, what about using all four through one platform for around US$20 a month?

That was enough to send me further down the rabbit hole.

The problem is that they aren’t identical products competing to do exactly the same job.  They have different models, tools, strengths, and increasingly different specialist environments, and even saying “I use ChatGPT” isn’t specific enough.

Which ChatGPT model?

Are you using ChatGPT itself, ChatGPT Work or Codex?  Likewise, using Claude in a browser isn’t the same as using Claude Code inside a development project.  Then there are services such as Bluehost AI All-Access that put models from several different AI companies into one dashboard.

Welcome to the next phase of AI confusion, or, as I prefer to think of it:  Nerd alert — but useful nerd alert.

The good news is that once you stop trying to find one AI that wins everything, choosing becomes much easier.

My rule is now: Don’t ask which AI is the best. Ask “which AI” is best for this particular job.

The short version: For those who want the TL;DR, if you don’t want to read the entire deep dive, here is my basic division of labour.

The most important distinction is this: ChatGPT plans and coordinates. Claude implements and edits. Gemini processes and examines. Grok challenges and sparks ideas.

That is not a rule carved in stone, as all four can overlap, and the difference is where I would instinctively start.

How well do the four platforms suit different jobs?

Before the AI purists come for me, a warning about this table.

Modern frontier AI models can perform an enormous range of tasks. A ⚠️ does not mean that the model cannot do the job. It means it would not necessarily be my first choice.

Legend

✅ Strong choice
⚠️ Capable, but another platform may be stronger for this particular job
❌ Feature or product is genuinely not included / not designed for that purpose

My personal favourite for managing the entire journey is still ChatGPT; however, that does not mean I expect it to win every individual stage.

ChatGPT: my all-round project partner

ChatGPT is the platform I tend to use as my central workspace. That doesn’t automatically make it the best at every task.  It’s particularly useful when something begins as a vague idea and eventually needs to become a finished result. For example, I might move through:

1. Research the subject.

2. Work out what matters.

3. Compare different approaches.

4. Decide on an angle.

5. Create a structure.

6. Draft the content.

7. Review supporting files.

8. Create visual material.

9. Prepare SEO.

10. Adapt the work for social media.

11. Create a publishing plan.

12. Work out what I actually need to do next.

ChatGPT is particularly useful at connecting those stages rather than treating each one as an isolated question. I often begin with something incredibly sophisticated such as:  “I have an idea…”

From there, I can gradually develop the idea into something useful.  That is one of AI’s most underestimated abilities. Sometimes I do not need the answer yet.

I need help defining the question.

ChatGPT Plus and the OpenAI API are not the same thing

This is where model descriptions become confusing.  OpenAI has a developer model catalogue containing models available through its API.  That doesn’t mean every model listed on the developer website automatically appears as a selectable model in a standard ChatGPT Plus chat.

OpenAI’s current developer catalogue includes:

• GPT-6 Astra

• GPT-5.6 Sol

• GPT-5.6 Terra

• GPT-5.6 Luna

OpenAI currently describes Astra as its most capable model for the hardest end-to-end work, Sol as the GPT-5.6 flagship for complex professional work, Terra as the balance between intelligence and cost, and Luna as the model optimised for cost-sensitive, high-volume workloads.

But there is a product distinction.

In ChatGPT itself, GPT-5.6 Sol is rolling out across eligible paid plans, with Plus receiving Medium and High reasoning. Terra and Luna are also available through OpenAI products such as Work and Codex for eligible paid accounts, while API access is billed separately.

And as I write this on 12 September 2026, GPT-6 Astra has only just begun rolling out. OpenAI says Plus, Pro, Business and Enterprise access is coming during the rollout rather than appearing instantly for everybody.  That date matters, because this landscape moves absurdly quickly.

Which OpenAI model should you use?

OpenAI model quick guide

GPT-6 Astra: use it for the hardest work

Astra is OpenAI’s new flagship. This is not the model I would waste on:

“Write five alternative Instagram captions about Sunday brunch.”

I would use it when the problem itself is difficult. Examples include:

• Complex strategic analysis

• Difficult research

• Large multi-stage projects

• Major coding problems

• Software engineering

• Computer-use workflows

• Complicated professional documents

• Integrating information across many sources

• Reviewing a plan for hidden weaknesses

• Tasks where several interconnected decisions need to be made

OpenAI describes Astra as its most capable model for complex reasoning, coding, computer use, research and document creation.  In simple terms:

Use the biggest brain when the problem actually deserves the biggest brain.

GPT-5.6 Sol: my serious everyday thinking model

GPT-5.6 Sol is the model I would use for most substantial ChatGPT work.  It is particularly suited to:

• Research

• Business strategy

• Articles

• Project planning

• Decision support

• Website architecture

• Analysing documents

• Comparing options

• Technical troubleshooting

• Coding

• Complex writing

• Organising complicated information

OpenAI describes Sol as its flagship GPT-5.6 model for complex professional work.  Paid ChatGPT users can also control how much reasoning effort Sol applies to a problem. That is important. Not every question deserves a miniature parliamentary inquiry. 

Sometimes I want: Quick answer.

Other times I want: Think properly before you tell me what to do.

Being able to vary the thinking effort means I do not necessarily need to swap platforms every time the complexity changes.

GPT-5.6 Terra: intelligence without always using the heavyweight

OpenAI positions Terra as the model that balances intelligence and cost.  That language is particularly relevant for developers using APIs, where every token costs money. For the everyday user, I interpret the principle more simply. Terra is suitable when I need substantial capability but don’t necessarily need the highest-tier model. For example:

• Article drafts

• Website content

• Research summaries

• Structured analysis

• Everyday coding

• Business documents

• Content planning

• Routine professional tasks

Think of it as the sensible middle ground.

GPT-5.6 Luna: speed and production

Luna is designed for cost-sensitive, high-volume workloads. This is exactly the kind of AI I would use for:

• Meta descriptions

• Social-media variations

• Short summaries

• Extracting information

• Reformatting

• Creating lists

• Headline options

• Product descriptions

• Routine email drafts

• Categorising information

• Creating ten versions of something that already exists

There is little point in making a frontier reasoning model spend its computing life changing “Father’s Day in Adelaide” into 17 different social captions. Use the expensive brain for expensive problems. Use the fast brain for production.

What about GPT-4.1?

GPT-4.1 is older than the GPT-5.6 family, but I wouldn’t dismiss it just because a newer number exists.  OpenAI describes GPT-4.1 as a non-reasoning model with particularly strong instruction-following, tool calling, coding and long-context performance. That makes it useful when I already know precisely what I want. For example:

“Take this information, preserve every heading, do not add anything, convert the dates to this format and return it as a table.”

That is different from:

“Here is a business problem. Work out what I am missing.”

The second requires more reasoning. The first requires disciplined instruction following.

My OpenAI rule

If I had to reduce the current OpenAI family to one line:

Astra for the hardest work. Sol for serious everyday thinking. Terra for balanced professional work. Luna for speed and volume. GPT-4.1 for precise instruction-following.

Simple enough. Until they release another model next Tuesday.

ChatGPT is now more than a chatbot

There is another important shift happening. ChatGPT itself is becoming a collection of working environments. OpenAI currently distinguishes between:

Chat

For conversation, questions, research and everyday assistance.

Work

For longer, multi-step work and creating finished deliverables.

Codex

For software development and technical work.

OpenAI describes Codex specifically as an AI coding agent that helps users write, review and ship code. It is included across ChatGPT plans, although usage limits vary by plan. This matters when we compare ChatGPT with Claude, because Claude has exactly the same important distinction.

Claude: the implementation partner and careful editor

Claude has become particularly well known for coding, technical work and polished writing.  I tend to reach for Claude when something already exists, and I want to improve it. For example:

• Editing an article

• Removing repetition

• Making writing sound more natural

• Reviewing website copy

• Working through code

• Refactoring files

• Improving CSS

• Understanding an existing project

• Finding inconsistencies

• Making coordinated changes across several files

• Reviewing technical implementation

Claude often feels less like: “Help me think of an idea” and more like: “Here is the thing. Help me make the thing better.”

That distinction suits the way I work.

Claude is an excellent editor

Claude can be particularly useful when I want to identify:

• Repetition

• Awkward phrasing

• Unnatural transitions

• Excessive explanation

• Corporate-sounding filler

• Writing that feels generic

• Sentences that are technically correct but unpleasant to read

A prompt I might use is:

“Edit this for clarity, flow and naturalness. Preserve the facts, structure and personality. Do not make it sound generic, overly promotional or as though a robot has swallowed a corporate communications handbook.”

That last part is important. AI should improve my writing. It should not erase me from it.

Which Claude model should you use?

Anthropic currently has several Claude tiers with different strengths.  Among the models relevant to this article are:

Claude Haiku 4.5 was designed around speed and efficiency while retaining substantial coding capability.

Claude Sonnet 5 substantially improved Anthropic’s coding, reasoning, tool-use and agentic performance and is the default model on Claude’s Free and Pro plans.

Claude Opus 5 sits above it for more demanding professional and software-engineering workloads and long-running agents.

Claude Code is not a Claude model

This distinction is extremely important.

Claude Code is a product.

It is Anthropic’s coding agent. Instead of simply opening Claude and asking:

“Can you write some CSS?”

Claude Code works directly in a terminal or supported development environment. It can inspect the project, understand files, work through a codebase and make coordinated technical changes. Anthropic describes Claude Code as giving users access to Claude models directly in the terminal or supported IDEs for complex coding tasks. Claude Pro includes Claude Code access.

That means saying:

“Claude is better than ChatGPT for coding because of Claude Code”

is not quite a fair comparison. We need to compare equivalent products.

Claude Code vs Codex: the fair coding comparison

The genuine direct comparison is: Claude Code vs OpenAI Codex

And at the broader subscription level: Claude Pro vs ChatGPT Plus

Both Claude Pro and ChatGPT Plus are general-purpose AI subscriptions with access to specialist coding environments.

Claude Code vs Codex

Anthropic’s Pro plan is currently US$20 per month and includes Claude Code.  Codex is included across ChatGPT plans, with plan-dependent limits.

So which is better?

There is no honest universal winner.

I would choose Claude Code when:

• I am deeply focused on software development

• I have an existing codebase

• I need coordinated changes across files

• I like Claude’s coding style and development workflow

• I am spending significant time in a terminal or IDE

I would choose Codex when:

• ChatGPT already manages the wider project

• I want research, planning and coding within the same broader ecosystem

• I want an OpenAI coding agent connected to the rest of my ChatGPT work

• My technical work is only one part of a larger project

And I would test both against the same real-world project before declaring one the winner. Benchmarks are interesting. Your actual workflow is more important.

Gemini: the multimodal research workhorse

Gemini is particularly interesting when a project contains more than ordinary text. I would consider it for:

• PDFs

• Images

• Screenshots

• Charts

• Tables

• Large reports

• Research material

• Technical documentation

• Coding

• Visual website reviews

• Google-oriented workflows

• Mixed text-and-image source material

This is where the term multimodal becomes useful.

Some tasks are not:  “Read these paragraphs.”

They are:  “Here are three PDFs, two screenshots, a spreadsheet, a chart and a diagram. Work out what all of this means.”

That is a very different job.

Gemini models: Flash does not necessarily mean basic

One mistake is assuming that any model called “Flash” must be the dumb little fast version.  That is no longer necessarily true.  Google currently describes Gemini 3.7 Flash as a highly capable model for complex coding, multimodal reasoning, agentic workflows and multi-step execution.  Among the Gemini models relevant to the All-Access dashboard, I have been exploring:

Gemini 3.5 Flash-Lite is specifically positioned as a fast, cost-effective model for high-throughput execution.  So I would use Flash-Lite for things such as:

• Sorting lists

• Labelling data

• Extracting names and dates

• Generating multiple metadata variations

• Converting information into tables

• Repetitive summaries

• Processing many similar items

Again:  Do not pay the intellectual equivalent of a neurosurgeon to alphabetise your filing cabinet.

Gemini for websites

Gemini can also be useful when I want to look at the visual side of a website.  For example:

• Examine a screenshot

• Assess layout

• Compare a design to a brief

• Analyse spacing or hierarchy

• Generate HTML, CSS or JavaScript

• Review technical documentation

• Explore alternatives

• Work through complex visual source material

I might use Gemini to examine what a page looks like, Claude or a coding agent to work through the implementation, and ChatGPT to keep the work connected to the site’s purpose, audience, SEO and business model.  That is the “AI team” concept in practice.

Grok: no longer just the cheeky creative one

I originally thought of Grok primarily as the creative challenger, to be honest that is why i signed up with the four pack with blue host to expand my creative social media content, I still think that is one of its most useful roles.  I use the concept of Grok when I want questions such as:

“What is the strongest criticism of this idea?”

“What am I overlooking?”

“Give me five angles that are more interesting without becoming ridiculous clickbait.”

“How might people actually react to this?”

“What would a sceptical customer say?”

That ability to challenge the safe, sensible answer can be valuable; however, describing Grok only as the creative or social-media model is becoming outdated. Grok 4.6 is now positioned as a frontier model for coding, agentic tasks and knowledge work, with reasoning, web search, X search and code execution among its available capabilities.

So Grok belongs in serious technical conversations too.

Where I would still use Grok first

Even with its expanding technical abilities, I particularly like Grok’s place in the workflow as the challenger. For example:

• Alternative viewpoints

• Brainstorming

• Social-media hooks

• More conversational phrasing

• Testing an idea

• Challenging assumptions

• Looking for likely objections

• Exploring online conversation

• Creating a stronger angle

• Making an idea less predictable

Sometimes an answer can be intelligent, accurate and utterly forgettable.

That is when I want another voice in the room.

The important difference between a model and a product

By now you may have noticed something. We use the word “AI” to describe several different things. There are:

Platforms

ChatGPT
Claude
Gemini
Grok

Models

GPT-5.6 Sol
Claude Sonnet 5
Gemini 3.7 Flash
Grok 4.6

Specialist agents and working environments

Codex
Claude Code
ChatGPT Work
Other development agents and tools

Aggregators

Platforms such as Bluehost AI All-Access that provide models from several companies through one interface. These are not interchangeable concepts. Once you understand that distinction, AI starts making considerably more sense.

Bluehost AI All-Access: four AI families in one place

This is where I discovered an interesting alternative. I originally approached Bluehost as a website-hosting provider. Bluehost now also offers an AI All-Access Pack that combines access to ChatGPT, Gemini, Claude and Grok in one dashboard.

Bluehost says users can switch between models, compare responses and use built-in tools including a Research Agent, Presentation Builder and AI Article Writer. A Bluehost hosting plan isn’t required, and that is exactly why understanding the differences between the models suddenly becomes useful.

If several models are sitting in front of you, the question changes from:

Which subscription should I buy?

to:

Which model should I use for this particular prompt?

What Auto Route does

One particularly useful feature is Auto Route. Auto Route is not another AI model. It is a routing function.  Instead of choosing a model yourself, Bluehost says the system can determine which available AI model best suits the request.

For someone new to AI, that may be the easiest place to start. For somebody like me, who apparently now needs to know the personality traits of ten different language models, manually selecting them is half the fun.

The models I currently see inside AI All-Access

The precise model list can change as providers release newer versions. In the version of AI All-Access I am currently examining, the choices include models such as:

Faster / everyday options

• Auto Route

• GPT-5.6 Luna

• GPT-4.1

• Gemini 3.7 Flash

• Gemini 3.5 Flash-Lite

• Claude Haiku 4.5

Deeper-thinking options

• GPT-5.6 Sol

• GPT-5.6 Terra

• Gemini 3.1 Pro

• Claude Sonnet 5

• Claude Opus 5

• Grok 4.6

Bluehost also states that it adds new leading models to the All-Access platform as the available model range evolves.  That is important because any article listing exact model numbers will eventually date. The principle will not.

Which AI All-Access model would I choose?

Here is the simple version I would keep next to my computer.

That table is not a ranking. It is a routing guide.

AI All-Access is not four complete native subscriptions

This distinction is important. Accessing an OpenAI model inside another platform is not necessarily the same experience as purchasing ChatGPT Plus. Likewise, having access to Claude Sonnet or Claude Opus inside an aggregated dashboard does not automatically mean you have the complete Claude Pro product. For example:

Claude Code is a separate coding environment.

Likewise:

Codex is OpenAI’s dedicated coding agent.

Bluehost’s standard AI All-Access plan provides its models through the All-Access interface. Bluehost specifically says the All-Access subscription itself does not provide individual model API keys.

Bluehost separately offers AI Credits and an LLM Gateway for API and developer use, which is a different product and billing arrangement. Those credits can even be connected to tools such as Claude Code in certain server setups.

So there are really two different questions:

Do I mainly want access to several AI models?

or:

Do I want the complete native ecosystem of one particular AI company?

That distinction determines whether an aggregator or a native subscription makes more sense.

ChatGPT Plus vs Claude Pro vs AI All-Access

This may be the easiest way to see the difference.

✅ = included/core feature

⚠️ = available differently or with limitations

❌ = not included in that subscription itself

*Bluehost separately offers AI Credits that can be connected to Claude Code in supported environments; that is separate from the standard All-Access subscription.

The takeaway is simple.

Choose ChatGPT Plus if:

You primarily want the full OpenAI ecosystem.

That includes the broader ChatGPT experience and access to OpenAI specialist environments such as Codex.

Choose Claude Pro if:

Claude is your preferred AI and Claude Code is particularly important to the way you work.

Consider AI All-Access if:

Your priority is switching between AI providers, and you value having ChatGPT, Claude, Gemini and Grok available from one dashboard rather than maintaining several separate subscriptions.

Is one AI subscription enough?

For many people:  Absolutely. If all you do is:

• Ask everyday questions

• Draft occasional emails

• Summarise information

• Generate ideas

• Write simple content

you probably do not need an elaborate AI command centre. Pick the platform you enjoy using and get on with your life. But if your work regularly crosses several areas — research, writing, websites, coding, strategy, documents, images and content production — understanding the strengths of different models becomes considerably more useful. That does not necessarily mean paying for four separate subscriptions. It means learning how to route work intelligently.

How I use AI platforms together

This is where everything comes together.  The best results do not necessarily come from asking one AI to do everything.  They often come from giving different parts of the job to different tools.

For writing an article

1. ChatGPT

I would use it to:

• Define the subject

• Research the structure

• Identify important questions

• Create the outline

• Develop the article

• Keep track of what has already been decided

2. Gemini

I might use it to:

• Process long reports

• Examine PDFs

• Analyse images and charts

• Extract information from source material

• Compare complicated documents

3. Claude

I might use it to:

• Improve flow

• Remove repetition

• Make the writing more natural

• Check readability

• Review awkward sections

4. Grok

I might ask it to:

• Challenge the article’s premise

• Find a stronger angle

• Suggest unusual hooks

• Identify objections

• Think about how the subject may be received online

5. ChatGPT again

Then return to the central workspace to:

• Finalise the structure

• Incorporate the useful feedback

• Create headings

• Prepare SEO

• Produce social-media versions

• Develop the publishing plan

That is very different from putting the identical prompt into four chat windows and declaring whichever answer sounds nicest the winner.

For building a website

I’m currently exploring this by installing MPC plug-ins, this is another good example.

ChatGPT

I would use it to work out:

• What the website is for

• Who the audience is

• What pages are required

• What categories make sense

• What should be published first

• How the website might earn income

• What the user journey should be

• What the development priorities are

• What needs to happen next

Claude / Claude Code

I would consider it for:

• Understanding an existing codebase

• Refactoring

• Working across files

• Building components

• Fixing technical problems

• Improving responsiveness

• Implementing website changes

Gemini

I would use it for:

• Examining screenshots

• Looking at visual layouts

• Reviewing large technical documents

• Comparing design ideas

• Exploring coding alternatives

• Multimodal analysis

Grok

I would use it to ask:

• Is this concept actually distinctive?

• What is boring about the offer?

• What would make somebody care?

• What am I overlooking?

• Is there a more interesting way to monetise this?

Different job.

Different brain.

For social media

My workflow might be:

1. ChatGPT — define the message, audience and purpose.

2. Grok — create sharper or less predictable hooks.

3. Claude — polish the wording.

4. Luna, Flash-Lite or Haiku — create multiple platform variations quickly.

5. ChatGPT — organise the final publishing schedule.

This prevents every post from becoming:

“We are thrilled to announce…”

Nobody is that thrilled.

For research and decision-making

I would use the platforms differently again.

Gemini

Process large or visual source material.

ChatGPT

Organise the information, compare options and structure the decision.

Grok

Challenge the prevailing view.

Claude

Review the logic and explain the conclusion clearly.

ChatGPT

Turn the decision into an action plan.  For medical, legal, or financial issues, treat AI as an assistant rather than the final authority.  It can help identify questions, organise evidence, find primary sources and explain complicated information.  Important decisions still deserve reliable primary evidence and appropriately qualified professional advice.

Speed task, everyday task or deep-thinking task?

One of the most useful habits I have developed is deciding how much intelligence a task actually requires.

Before choosing a model, I now ask:

Is this a speed task?

Examples:

• Extract these dates

• Rewrite this caption

• Give me ten headings

• Sort this list

• Summarise this paragraph

Use a lightweight model.

Is this an everyday professional task?

Examples:

• Draft an article

• Review a business document

• Analyse a website page

• Plan a campaign

• Compare several options

Use a good balanced model.

Is this genuinely difficult?

Examples:

• Develop a complicated strategy

• Analyse conflicting evidence

• Debug a complex technical problem

• Review a major decision

• Work across a large project

Use the stronger reasoning model.  This sounds obvious.  Yet we routinely use the largest AI model available to perform jobs that amount to changing a comma.

Coding question or coding agent?

Developers and website owners should ask one more question.

Do I simply need help with code, or do I need an AI agent working inside the project?

Those are different things.

Ask an ordinary AI model when:

• You want a code snippet

• You want something explained

• You want an error interpreted

• You want CSS suggestions

• You want a technical concept translated into plain English

Use a coding agent when:

• The project contains many files

• Changes affect several components

• The AI needs to inspect the actual codebase

• Commands need to run

• Tests need to be performed

• Changes need to be tracked

• The problem must be traced through an existing project

That is when tools such as Claude Code and Codex become significantly more interesting.

My current AI workflow

At the highest level, I now think of my work as:

Research → Think → Write → Build → Publish → Organise

And the AI team fits around it like this:

This is not about becoming dependent on AI.  It is about understanding which tool removes friction at which stage.

What I have learned about using AI effectively

The biggest improvement in my results has not come from discovering one miraculous model.  It has come from asking better questions about the task itself.  Before opening an AI, I now ask:

• Do I need research?

• Do I need creativity?

• Do I need a decision?

• Do I need something written?

• Do I need something edited?

• Do I need code?

• Do I need an AI coding agent?

• Do I have large files?

• Do I have visual information?

• Do I need current information?

• Do I need a second opinion?

• Do I need speed?

• Do I need deep reasoning?

• Do I need the result turned into an actual plan?

The answer usually tells me which tool to reach for.

My simple AI division of labour

If everything above has now made AI seem more complicated rather than less complicated, come back to this.

ChatGPT

Think, plan, write and organise.

Claude

Implement, code and edit.

Gemini

Process, examine and research.

Grok

Challenge, brainstorm and offer another angle.

Lightweight models

Produce, extract and repeat quickly.

Claude Code / Codex

Work directly on software projects.

AI All-Access

Give me several AI families without making me live inside four subscriptions.

While comparing ChatGPT, Claude, Gemini and Grok, I stumbled across something I wasn’t expecting: Bluehost AI All-Access, which gives you access to models from all four AI families in one dashboard for around US$20 a month.

That immediately caught my attention because the alternative is managing multiple separate subscriptions — and multiple logins, billing accounts and platforms — just to access different AI tools. There is also a practical security and simplicity angle here. Instead of creating and maintaining separate accounts across several providers, AI All-Access gives you one central place to switch between models, compare responses and use different tools depending on the job.

For someone like me, who likes testing different AI platforms but doesn’t necessarily want four separate subscriptions running at once, it’s a surprisingly useful setup, which is really the whole article. Everything else is detail.

A note about Bluehost AI All-Access: For readers who want access to several AI families without subscribing to each separately, Bluehost’s AI All-Access Pack is an option worth considering.  It provides access to ChatGPT, Claude, Gemini and Grok from one dashboard, allows model switching and comparison, and includes additional tools such as a Research Agent and Presentation Builder. Bluehost says you don’t need a hosting subscription.

The key caveat is that this isn’t the same as owning the full native paid subscription from each AI company. If you specifically need features such as Claude Code or the wider ChatGPT/Codex ecosystem, compare the native subscription carefully against the aggregated option.  For somebody mainly interested in the models themselves, however, having several leading AI families available in one place makes the central argument of this article surprisingly practical:

Choose the AI according to the job.

Affiliate disclosure: This article may contain affiliate links. If you choose to purchase a product through one of my links, I may receive a commission at no additional cost to you. I only include services that are relevant to the subject and that I believe readers may genuinely find useful. I’m currently using Bluehost AI All-Access and enjoying it, so I wanted to share it with readers who may find it useful too.

Final thoughts

Artificial intelligence has become part of everyday life so quickly that most of us are still working out how to use it properly.  AI is not simply a machine that answers questions.  It can be:

• A researcher

• A writer

• An editor

• A coding partner

• A developer

• A project planner

• A business strategist

• A creative sounding board

• A visual analyst

• A document organiser

• A production assistant

• A devil’s advocate

• A second opinion

But it becomes considerably more powerful once we stop pretending every AI is exactly the same.  No single model fits every task, and that is increasingly the point.

ChatGPT is my central project partner. I use it for everything from day-to-day problem-solving to creative work, research, writing, process improvements, repetitive production tasks and working through documents and legal citations. It is the platform I currently rely on most heavily.

Claude is the implementation partner and careful editor — although I’m still yet to use it properly myself. I’m interested in testing it more, particularly for editing, coding and website work.

Gemini is the multimodal research workhorse, although I haven’t used it extensively yet. Its strengths around large files, images and mixed source material are where I expect it to become more useful to me.

Grok is the challenger and creative wildcard, and I genuinely enjoy running ideas past it. I like using it to test an angle, challenge an assumption, sharpen social-media ideas or see how something sounds from a less predictable perspective.

Claude Code and Codex are where ordinary coding assistance becomes genuine agentic software development. I have friends who use Claude extensively across their businesses, including websites built with Claude Code, but I’m still exploring these tools myself rather than claiming first-hand expertise.

That version is much safer editorially because it separates what you personally use from what you know through others or are still exploring.

And lightweight models are where I stop wasting frontier-level computing power asking for twelve slightly different versions of an Instagram caption.

The model names will change.

The rankings will change.

Another flagship model will launch before half of us have learned how to pronounce the current one. But the skill that will remain useful is knowing what kind of work you are actually trying to do. So my biggest lesson after exploring all of them is still the simplest:

Do not ask which AI is the best. Ask which AI is best for this particular job.

Used properly, AI does not replace thinking. It helps me research more effectively, see different perspectives, work through complicated problems, move faster and finally make progress on the ideas that might otherwise remain permanently trapped in a notebook, a browser tab or that famous folder marked:

“I’ll get to that eventually.”

Thanks for reading the confessions of a closet nerd. Somewhere along the way, AI went from being a useful tool to something I genuinely enjoy pulling apart, testing and comparing. If this article saves you a few subscriptions, a few hours of confusion, or helps you choose the right AI for the job, then all that nerding out was worth it.

Now I’m off to ask four different AIs what I should investigate next.