30 AI Models Compared: OpenAI, Gemini & Claude (2026)

Which AI model is right for your business?

Start with the least expensive model that handles your customers’ real questions well. Pay more when testing shows that it solves a problem the cheaper option cannot.

That is the short answer. Here is why it matters.

Buying the biggest AI model to answer “What time do you close?” is like hiring a Michelin-starred chef to make toast.

The toast might be excellent. It is still an expensive way to make breakfast.

But ask that same kitchen to design a tasting menu for guests with different dietary needs, and the extra skill starts to make sense.

AI works much the same way. Some jobs need quick, clear answers. Others need careful thinking, several sources and a good understanding of what could go wrong.

This guide compares 10 OpenAI choices, 10 Google Gemini choices and 10 Anthropic Claude choices: 30 in total. It includes current flagships, cheaper options and earlier releases that are still relevant. Google’s list includes one clearly marked custom-tools variant of its Pro model.

“Top” here means a useful shortlist for different jobs—not a claim that we have independently tested and ranked every model. Strengths reflect provider descriptions; the business use cases are our recommendations to test.

Model names and direct-provider prices checked on 13 October 2026. All prices are in US dollars. Availability can depend on your account and the platform you use.

Input and output prices, without the headache

Think of AI like a colleague reading a brief and writing a reply.

• Input: what it reads. Your customer’s question, your business instructions and the earlier conversation.
• Output: what it produces. The reply—and, for models that charge for it, extra internal thinking.

Providers measure this in tokens: small pieces of words and text. You do not need to count them yourself. Just know that longer questions, longer replies and more background information can mean a bigger bill.

The tables show price per one million tokens, the unit providers publish. That sounds enormous because it is a bulk rate, not the price of one message.

A $10 output price does not mean a $10 reply.

What our 20-message conversation estimate includes

Every row uses the same example: 10 messages sent by the customer and 10 replies received from the AI.

We assume:

• Each customer message uses 100 tokens, roughly 75 English words.
• Each AI reply uses 200 tokens, roughly 150 English words.
• The AI reads 500 tokens of business instructions before each reply.
• It also rereads the earlier messages so it can follow the conversation.
• No discounts for reusing text, and no extra internal thinking.

With that growing conversation history, the example uses 19,500 input tokens and 2,000 output tokens altogether. It is a medium-length chat, not ten one-word questions.

For anyone checking the numbers: estimated cost = input price × 0.0195 + output price × 0.002. Estimates are rounded to five decimal places.

These are text-model cost estimates, not your complete chatbot bill. They exclude platform subscriptions, setup, taxes, searches, external tools, voice, images and extra thinking. Models count text differently, too: the word counts are only a guide. Real conversations will vary.

We use standard paid rates, not free allowances or slower batch discounts, and the lower prompt-length price where a provider has more than one band.

Scroll the tables sideways to see all seven columns. On a phone, swipe across them.

10 OpenAI models: from everyday jobs to heavy thinking

OpenAI’s current range gives you a clear choice: Luna for focused, high-volume work, Sol for a middle ground and Astra for demanding tasks.

That does not mean the others suddenly become useless. An earlier model that already works well for your business may still deserve a place on your shortlist.

A practical example: a property agent asks for a buyer’s location, budget and preferred viewing time. That is a focused conversation. Start by testing Luna, not the most expensive model on the page.

Now change the job. Someone wants to compare several properties, understand conflicting requirements and weigh up a long list of documents. A stronger model may earn its higher price.

GPT-5.5 Pro deserves a special warning: OpenAI says some requests can take several minutes. It is not an obvious choice for a customer expecting a quick chat reply.

10 Google Gemini choices: fast answers, lower-cost work and deeper analysis

Google’s Flash models are worth testing when you want capable everyday responses. Flash-Lite options are aimed at keeping busy workloads affordable. Pro is the more demanding-work option.

The list deliberately avoids counting automatic aliases as different models. Custom Tools is a separate, officially documented Pro endpoint, not a completely different base model. It is included because it changes which tools the agent prioritises.

*Temporary prices: Google lists the Gemini 3.8 Flash and 3.6 Flash rates above through 31 December 2026. From 1 January 2027, their listed standard rates become $1.50 input and $7.50 output per million tokens. Our example would then cost about $0.04425 per chat, before extras.

“Preview” means an early-access release. Test it carefully and check the provider’s update and retirement notices before making it central to your business. The Custom Tools variant is mainly a developer choice, not the default recommendation for a small-business chat widget.

A practical example: a trades business receives “Do you cover my area?”, “Can I send photos?” and “When can you call me back?”

A lower-cost model may be perfectly capable of collecting those details and organising the enquiry. If the job becomes reading a long specification and comparing several options, test Pro or a more capable Flash model.

The useful question is not “Is it Google?” It is “Does it handle our actual job well?”

10 Anthropic Claude models: quick helpers to detailed problem-solvers

Claude’s range has a similar shape. Haiku is the high-volume helper. Sonnet balances speed and intelligence. Opus handles more demanding work. Fable is aimed at particularly difficult reasoning and longer tasks.

Think of it as a team, not a podium. You do not ask your most senior specialist to sort every incoming email.

These ten are listed as active on Anthropic’s model-status page at the review date. That is not a promise they will remain available indefinitely.

Haiku 5.5’s prices here apply to prompts up to 100,000 tokens. Bigger prompts have higher rates. Our sample is well below that limit.

A practical example: a clinic needs to collect an enquiry, find out which service someone wants and pass it to the right team. Test Haiku for those focused steps.

A long, carefully worded response to a complicated complaint is a different job. Sonnet or Opus may be worth testing—with human approval where the situation calls for it.

No model should be left to improvise medical advice or promise a refund it cannot authorise.

Why pay nearly $100 for 100 chats if a cheaper model can do the job?

Here is a real price comparison using our sample, not a made-up “Luna” example:

• 100 chats with GPT-5.5 Pro: approximately $94.50 in the model’s text charges.
• 100 chats with GPT-6 Luna: approximately $0.30.
• Difference: approximately $94.20.

Same assumed amount of text. Very different model rates. Not a claim of equal answers or equal thinking effort. Additional internal thinking can raise the bill.

The cheaper model is not automatically the right one. But the expensive one needs a reason to be there.

If both correctly answer opening-hours questions, capture contact details and send the enquiry to the right person, paying more has not improved the outcome.

It is like booking a removal truck to carry one shopping bag. The extra capacity exists. You are just not using it.

Now imagine the cheaper model repeatedly misunderstands an important request. Your team spends time fixing it. Customers give up. Bookings go wrong.

That changes the comparison. Saving a few dollars on AI and creating an hour of extra work is not good value.

Choose the cheapest model that passes the test—not the cheapest model regardless of the result.

Match the model to the conversation

“What time do you close?”

Start small. GPT-6 Luna, Claude Haiku 5.5 or Gemini 2.5 Flash-Lite are sensible low-cost candidates to test.

Give them the correct opening hours. Make the answer short. Do not send your entire company archive to answer one question.

“Can I get a quote?”

Often, the hard part is not intelligence. It is asking the right questions.

What service? Which area? When is it needed? What is the best way to follow up?

A focused, lower-cost model plus a clear conversation flow can do this well. It should collect details, not invent a final price when the quote needs a person.

See our guide to chatbots for lead generation for what useful information capture looks like.

“Which of these options fits my situation?”

Now there may be several requirements to weigh up. Start testing the middle ground: GPT-6.1 Sol, Claude Sonnet 5.5 or Gemini 3.8 Flash.

An example: a travel enquiry involving different dates, accessibility needs, a budget and several travellers. More capable reasoning may make the conversation clearer.

“Read these documents and work through the difficult bits”

This is where stronger models can justify their cost.

Consider GPT-6 Astra, Claude Opus 5.5, Claude Fable 5.1 or Gemini 3.1 Pro Preview. Test the exact documents and questions first.

For legal, medical or financial decisions, a stronger model is still not a substitute for appropriate professional review.

Three things that can matter more than the model name

1. Give it the right information

The smartest assistant cannot know that your opening hours changed yesterday unless you tell it.

A well-informed cheaper model can be more useful than an expensive model guessing from old information.

Think of it like a receptionist with the wrong diary. Hiring someone more experienced will not fix the diary.

2. Keep the useful steps clear

Answer the question. Collect the details. Confirm what matters. Save the enquiry. Hand over when needed.

That sounds simple because it should be. A clever reply is not the same as a booking saved in your calendar.

3. Keep replies as long as they need to be—and no longer

“We close at 6 pm” is usually better than three paragraphs about your commitment to customer convenience.

Short, helpful answers can improve both the customer experience and the bill.

The goal is not to make every reply tiny. It is to avoid making customers read a speech when they asked a simple question.

Test three models before you choose one

Pick a low-cost option, a middle-ground option and a stronger option.

Then give each the same real business scenarios:

• A straightforward question.
• A customer sharing several details in one message.
• A misspelt address or unusual name.
• A question your business information does not answer.
• A request outside your service area.
• An upset customer.
• A booking change.
• A request to speak to a person.

Check whether it answers correctly, follows your rules, captures details accurately and knows when to stop.

Measure response time and cost per successfully handled conversation, not just cost per message. If it sounds wonderful but saves the wrong phone number, it has failed a very basic job.

You may find that a cheaper model covers most routine enquiries and a stronger one is useful for particular cases. That split needs to be designed and tested; it is not something every chatbot platform does automatically.

Where ChitChatBot.ai comes in

The model is one part of the setup. Your business still needs the right information, conversation design, customer channels, saved contact details and a clear next step.

ChitChatBot combines AI conversations with flows and configured actions so an enquiry can become something useful: a qualified lead, a follow-up or a handover to your team.

We do not recommend choosing a model just because its name is on the latest launch announcement. We recommend choosing around your customers, your workload and your budget.

Our done-for-you service can help you design and test that setup. Model availability and billing depend on the platform and configuration: this comparison is not a claim that all 30 options are available inside ChitChatBot, or that these direct-provider rates equal your ChitChatBot bill.

Frequently asked questions

Is the most expensive model the best?

For some difficult tasks, it may be the best fit. For routine customer conversations, you may be paying for capability you do not need. Test the job, not the reputation.

Does a 20-message chat have a fixed price?

No. Ten short questions and ten long questions are different workloads. Earlier messages, business instructions, extra thinking and connected tools can all change the cost.

Are these ChatGPT, Gemini or Claude subscription prices?

No. They are direct-provider API usage rates: the charges for using models inside an application. Consumer subscriptions and chatbot-platform subscriptions are separate.

Should I always choose the newest version?

Not without testing. New releases can improve quality or price, but they can also respond differently. Check your key conversations before switching.

Can a better model fix a badly designed chatbot?

Not reliably. It cannot repair missing information, broken bookings or unclear handovers just by being more intelligent.

Sources and price notes

Prices and model descriptions come from the providers’ official documentation, reviewed on 13 October 2026:

• OpenAI API pricing, including its full pricing data, and model catalogue.
• Google Gemini API pricing, model retirement notices and Gemini 3.1 Pro variant details.
• Anthropic Claude pricing, model overview and model status.

Standard text rates only. No cached-input discounts, batch discounts, extra thinking, long-prompt surcharges, regional uplifts or tool fees are included in the estimates. These are planning examples, not live bills or independent performance benchmarks.

The best model is the one that gets your customer to the right next step—without making you pay for skills the conversation never needs. Talk to us about your AI setup.