There is no universally best AI model. There are models that are better for a particular workload, risk level, latency target, tool environment, and budget. This guide gives you a useful shortlist, then shows you how to test it against your own work.

Prices below are standard text-token rates checked against provider documentation on August 9, 2026. Chat subscriptions and API usage are separate products. Always verify the provider page before committing a production architecture.

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OpenAI model guideGPT-5.6 Sol, Terra, and Luna: access, pricing, and which one to use

A practical guide to the GPT-5.6 model family, including Sol, Terra, Luna, API pricing, context limits, reasoning settings, access, and workload selection.

Open page →Anthropic model guideClaude Fable 5, Opus 5, and Sonnet 5: what each model is for

Compare Anthropic's Claude Fable 5, Opus 5, and Sonnet 5 models by access, price, context, latency, coding ability, and production use.

Open page →Google model guideGemini 3.1 Pro and Gemini 3.6 Flash for multimodal and agentic work

A practical guide to Gemini 3.1 Pro Preview and Gemini 3.6 Flash, including multimodal capabilities, API access, 1M context, pricing tiers, and workload choice.

Open page →xAI model guideGrok 4.5: pricing, access, search tools, and practical use cases

Learn when to use Grok 4.5, how to access it through Grok and the xAI API, what token and long-context pricing costs, and where search tools change the workflow.

Open page →Model evaluation guideHow to choose an AI model using your own work instead of benchmarks

Build a practical AI model evaluation, compare efficient, balanced, and flagship models, score quality and cost, and create a routing policy for production.

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The shortlist that is actually useful

OpenAI's GPT-5.6 family divides one generation into Sol, Terra, and Luna. Sol is the flagship, Terra is the balance of capability and cost, and Luna is intended for efficient high-volume work. Anthropic's current line uses Fable for maximum broadly available capability, Opus for complex agentic and enterprise work, and Sonnet for faster production workloads.

Google's Gemini line remains compelling when documents, images, audio, and video belong in one workflow. Gemini 3.1 Pro Preview is the quality-first option while Gemini 3.6 Flash is the faster generally available model. xAI's Grok 4.5 combines reasoning with first-party web and X search tools, which can simplify workflows that require current public information.

How to choose without guessing

Build a small evaluation set from your real inputs. Include clean examples, incomplete material, conflicting instructions, long documents, tool failures, and questions that cannot be answered from the evidence. Define a pass rule before running anything.

Test one efficient model, one balanced model, and one flagship model with the same instructions. Score factual accuracy, required evidence, format compliance, latency, and total cost. The cheapest model that passes is the right default; difficult or ambiguous cases can route upward.

  • Use exact model IDs in production when repeatability matters.
  • Measure reasoning settings separately; more reasoning can add latency and output tokens without improving every task.
  • Include tool fees, search calls, cache writes, and long-context tiers in the real cost model.
  • Re-run the evaluation when a provider changes an alias or announces a retirement.
Model routing usually saves more money than squeezing a few sentences out of the prompt.

Chat access and API access are different decisions

Use ChatGPT, Claude, Gemini, or Grok when a person is working interactively. Use an API when software must call the model, enforce a schema, use tools, log outcomes, or run repeatedly. A paid chat plan does not normally include API credits, and an API balance does not automatically upgrade the consumer chat product.

Before creating a key, decide who owns the account, where the secret will live, which project will be billed, and what spending limit is acceptable. Put keys only in server-side secret storage. Never place them in a public browser bundle or repository.

Interactive API estimate

Turn token rates into a workload cost

Uses standard uncached text-token prices. Tool calls, caching, batch discounts, priority service, and long-context tiers can change the bill.

Estimated cost$0.20GPT-5.6 Terra · $2.5/M input · $15/M output

1.05M context

Primary sources

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