GPT-6 vs Gemini 4 Argon vs Claude Opus 5.5: which AI model should a business use?

Three frontier AI models arrived within four weeks: Anthropic's Claude Opus 5.5 on 22 September, OpenAI's GPT-6 in ChatGPT on 7 and 8 October, and Google's Gemini 4 Argon on 13 October. On reported prices, GPT-6 Sol and Gemini 4 Argon are the cheapest for now, Claude Opus 5.5 costs about twice as much, and all three can read around a million tokens at once. Which one a business should use depends less on headlines than on testing each model on its own tasks.

What launched, and when

• Claude Opus 5.5 (Anthropic) was released on 22 September 2026. Reported pricing is $4 per million input tokens and $20 per million output tokens, 20% below the previous Opus model, with a 1 million token context window and no extra charge for long prompts.
• GPT-6 (OpenAI) rolled out across ChatGPT on 7 October, reaching Free and Go users on 8 October. Paid plans use GPT-6 Sol and free tiers use the lighter GPT-6 Luna. It arrived with Intelligent UI, which lets ChatGPT answer with charts, forms and buttons instead of only text. Third-party price trackers list GPT-6 Sol on the API at about $2 per million input tokens and $10 per million output tokens, with a context window of roughly 1.05 million tokens.
• Gemini 4 Argon (Google) became generally available in the Gemini API on 13 October. Its introductory price is reported as $2 per million input tokens and $10 per million output tokens until 30 November, doubling to $4 and $20 from 1 December. It is listed as paid-only on the API.

How they compare

• Price today: GPT-6 Sol and Gemini 4 Argon are level at about $2 / $10. Opus 5.5 is about twice that at $4 / $20.
• Price from December: Gemini 4 Argon is reported to rise to Opus 5.5's level, leaving GPT-6 Sol the cheapest of the three.
• Long documents: all three are in the million-token range. Opus 5.5 is reported to charge the same rate across its full window, while GPT-6 Sol is reported to charge more once a prompt passes 272,000 tokens.
• Benchmarks: the published numbers mostly come from the vendors and they disagree. On Terminal-Bench 4.0, a test of agent-style coding work, Google's own table shows Opus 5.5 at 66.4% and Gemini 4 Argon at 57.4%, while Google reports Argon ahead on other tests. Treat any single leaderboard with caution.

Prices here come from provider pages as reported by third-party trackers and may change. Check each provider's pricing page before you budget.

What it means for businesses

For most companies, the model matters less than the setup around it.

• Test on your own work. Run 20 real tasks, such as customer replies, invoice extraction or report summaries, through each model and compare quality and cost. Benchmarks rarely match your data.
• Use small models for routine jobs. Most day-to-day automation does not need a frontier model. In our WhatsApp chatbot cost guide, a small model handles thousands of replies for a few dollars a month.
• Stay model-agnostic. The leader changes every few weeks. Build automations so the model can be swapped without rewriting the workflow; our business process automation work is built that way.
• Keep the guardrails. A smarter model still needs its own account, limited access and a person approving risky steps, as covered in our AI agent security basics.