Claude, GPT-6 or Gemini 4? Choosing an AI model

There is no single best AI model in late 2026. Anthropic, OpenAI and Google each released several strong models this year, and their prices now overlap closely. Choosing an AI model is about which one suits each task in your business.

API prices side by side

Standard API prices in US dollars per million tokens, as published in early November 2026.

Model	Input	Output
Claude Fable 5.1	US$10	US$50
GPT-6 Astra	US$10	US$50
Claude Opus 5.5	US$4	US$20
Gemini 4 Argon*	US$2	US$10
Claude Sonnet 5.5	US$2	US$10
GPT-6.1 Sol	US$2	US$10
Gemini 3.6 Flash	US$1.50	US$7.50
Gemini 3.8 Flash*	US$0.75	US$3.75
Gemini 3.5 Flash-Lite	US$0.30	US$2.50
Claude Haiku 5.5	US$0.10	US$0.50

* Introductory prices. Gemini 4 Argon rises to US$4 and US$20 after 30 November 2026. Gemini 3.8 Flash rises to US$1.50 and US$7.50 from 1 January 2027.

Claude prices are from Anthropic’s pricing page. Gemini prices are from the launch posts for Gemini 4 Argon, Gemini 3.8 Flash and Gemini 3.6 Flash and 3.5 Flash-Lite. GPT-6 prices are Microsoft Foundry’s Global Standard prices for short prompts. GPT-6.1 Sol costs one-fifth of Astra’s standard API prices.

Some prices have conditions. Claude Haiku 5.5 costs US$0.50 and US$2.50 for prompts over 100,000 tokens. GPT-6 models cost more for long prompts. OpenAI also offers GPT-6.1 Terra and GPT-6 Luna at lower prices. Check OpenAI’s pricing page for those.

Why the price per token is only part of the cost

Two models with the same price per token can cost different amounts for the same job.

• Tokens are counted differently. Each provider splits text into tokens its own way. Claude Sonnet 5’s tokenizer produces about 30% more tokens for the same text than earlier models.
• Thinking adds output tokens. Models that reason before answering use more output tokens on hard questions. Claude and GPT-6 both let you set an effort level, and OpenAI’s GPT-6 model guide covers how to tune it.
• Caching cuts repeat costs. If you send the same instructions or documents many times, cached input costs much less. On Claude, a cache hit costs 10% of the normal input price or less. Gemini 4 Argon’s cached input is 95% off.

The reliable way to compare is to run the same real tasks on two or three models. Then compare the bill and the results.

Which tier suits which job

Top models (Claude Fable 5.1, GPT-6 Astra, and Gemini 4 Carbon once it opens up) suit the hardest work. Think complex analysis, difficult code and long agent tasks where mistakes are costly. Use them for the steps that need them, not for everything. Carbon is going to a group of cyber defenders first, and Google plans wider access “as soon as possible”.

Mid-range models (Claude Opus 5.5, Claude Sonnet 5.5, GPT-6.1 Sol, GPT-6.1 Terra and Gemini 4 Argon) cover most business work. That includes drafting, research, reports, customer replies and agents that use software.

Low-cost models (Claude Haiku 5.5, GPT-6 Luna, Gemini Flash and Flash-Lite) suit simple tasks at high volume. Examples are sorting enquiries, tagging data, pulling fields from documents and short summaries. Haiku 5.5 costs around 75% less to run than Haiku 4.5 on average.

A common pattern is to use a low-cost model for the first pass and a stronger model only when needed. For example, a cheap model sorts every incoming email. A stronger model then drafts replies to the few that need one.

Other things to weigh

• Where your work already happens. Gemini is built into Google Workspace apps. Microsoft 365 Copilot works inside Word, Excel and PowerPoint.
• Where you want to run it. The big models are now on several clouds. Claude’s latest models are on Amazon Bedrock, Google Cloud and Microsoft Foundry. GPT-6 is on Microsoft Foundry, and OpenAI announced its models are coming to Google Cloud.
• How often models change. Providers retire older versions regularly. Claude Sonnet 4.5 retires on 30 November 2026. Plan to retest your workflows a few times a year.
• Spending controls. Set a monthly limit on every API account, so a faulty automation cannot run up a large bill.

A simple way to choose an AI model

1. List the tasks you want AI to handle, and note how many times each runs per month.
2. Pick two candidate models for each task, one mid-range and one low-cost.
3. Run 20 real examples through both and compare quality, speed and cost.
4. Choose the cheapest model that meets your standard, and review the choice every few months.

For more on each family, read Every Claude release in 2026, GPT-6 explained and Gemini 4 Argon and Carbon explained.