AI models · Updated 2026-10-31

Which AI model should you use? (updated October 31, 2026)

A practical comparison of current Claude, GPT, and Gemini models, their API prices, context sizes, consumer plans, and places in a model suite.

The short answer

Keep two or three models in your suite. Use a balanced model for ordinary work, keep one stronger model for ambiguous or expensive mistakes, and send repeatable bulk work to a cheaper model. API list prices are not a direct forecast of a chat subscription bill: apps have plan limits, and API usage is charged separately.

Current choices

• Claude Opus 5.5 — daily driver for demanding mixed work. Anthropic positions it for long-running coding and knowledge work. API list price: $4 per million input tokens and $20 per million output tokens; 1 million token context. Claude Pro is $20/month and includes access to current Claude models, including Opus; subscription usage limits vary by plan. Fit in a suite: daily driver when quality and judgment matter more than the lowest token price.
• Claude Fable 5.1 — hardest long-horizon work. Anthropic calls it its most capable generally available model and recommends starting with Opus 5.5 for most workloads. API: $10/$50 per million input/output tokens; 1 million token context. It is available on Claude Pro, whose list price is $20/month. Fit: hard problems, when your own evaluations show Opus is not enough.
• Claude Sonnet 5.5 — fast, capable coding and everyday work. Anthropic describes it as strong at well-scoped everyday tasks, bug fixes, and polished documents. API: $2/$10 per million input/output tokens; 1 million token context. Claude Pro: $20/month; app limits vary. Fit: coding and well-bounded work where you want a capable default at a lower API rate.
• Claude Haiku 5.5 — repeated, narrow tasks. Anthropic points to summaries, classification, routing, and subagent work. API: $0.10/$0.50 per million input/output tokens for prompts up to 100,000 tokens; $0.50/$2.50 above that. Context: 1 million tokens, with higher rates above 100,000 prompt tokens. Claude Pro: $20/month; app limits vary. Fit: cheap bulk; check quality on the actual job before routing volume.
• GPT-6 Astra — OpenAI’s top model for difficult work. The model catalog describes it for demanding reasoning and coding. API: $10/$50 per million input/output tokens; 1.05 million token context. ChatGPT Plus is $20/month, with Astra available in Work and Codex, but Plus does not include GPT-6 Pro in Chat. API use is separate. Fit: hard problems and coding workflows that benefit from OpenAI’s tools.
• GPT-6.1 Sol — capable OpenAI work at a lower rate. OpenAI describes it as near-Astra performance for complex work at lower cost. API: $2/$10 per million input/output tokens; 1.05 million token context. ChatGPT Plus is $20/month, but plan access and limits depend on product and account. Fit: daily driver for OpenAI users who do not need Astra on every request.
• GPT-6 Luna — high-volume, focused work. OpenAI calls it its most efficient model for focused, high-volume tasks. API: $0.10/$0.50 per million input/output tokens; 1.05 million token context. Consumer access depends on current ChatGPT plan and model availability. Fit: cheap bulk for clear, repeatable work.
• Gemini 4 Argon — long-context research and multi-step work. Google describes it for complex coding, agent tasks, math, and science. API launch price through November 30 is $2/$10 per million input/output tokens, rising to $4/$20 on December 1; unified context is 1,048,576 tokens. Google AI Pro is $19.99/month and includes Argon in the Gemini app; API use is separate. Fit: coding or research that uses long context, and compare it on your own task before assigning it broadly.

A practical starting suite

• Daily driver: Opus 5.5 if Claude is your main app; GPT-6.1 Sol if you want OpenAI’s tools; Argon if your work centers on very long inputs.
• Hard problems: Fable 5.1 or GPT-6 Astra. Escalate only when a task needs their added reasoning or the cheaper model misses your acceptance checks.
• Cheap bulk: Haiku 5.5 or GPT-6 Luna for repeatable, narrow tasks. Test a sample first and send uncertain cases back to the stronger model.
• Coding: Start with Sonnet 5.5 or GPT-6.1 Sol for well-scoped changes. Reserve Opus, Fable, Astra, or Argon for larger migrations, ambiguous failures, or sustained work.

Putting API prices in perspective

At 2 million input tokens and 500,000 output tokens in a month, before caching, tools, taxes, or long-context multipliers, list-price API spend is about $18 on Opus 5.5, $9 on Sonnet 5.5 or GPT-6.1 Sol, $45 on Fable 5.1 or GPT-6 Astra, and $0.45 on Haiku 5.5 or GPT-6 Luna (assuming Haiku prompts stay at or below 100,000 tokens). Argon is $9 at its October introductory rate and $18 from December 1. Actual workloads vary, especially when a model uses more tokens to finish a task.

These are API calculations, not monthly app prices. Claude Pro and ChatGPT Plus are each $20/month; Google AI Pro is $19.99/month in the US. Those plans have changing access and usage limits, and API calls are billed independently. Check your model picker and the linked pricing page before relying on a plan feature.

What to do when a new model lands

Keep your current model as the baseline. Run the new release against the same real tasks, compare completed-work quality, time, and total cost, then switch only the route where it wins. A release note is evidence about what the vendor changed; it is not proof that the model is better for your own workload.