Model selection
The best model depends on the deliverable.
Choose an AI model and effort level by task, evidence needs, speed and visual requirements, with current ChatGPT and Claude guidance.
Updated
Choose the capability before the tier
A poster needs visual production and layout control. A report review needs source handling and analytical judgement. A code fix needs repository access and verification. First check that your environment has the required capability; then choose how much reasoning the task deserves.
| Task | Start with | Escalate when |
|---|---|---|
| Short rewrite or extraction | A fast text model and a clear example | It changes meaning or misses a subtle constraint |
| Report or multi-file work | A capable reasoning model with source files | Evidence conflicts or consequences need deeper scrutiny |
| Code change | A coding agent with the repository | The issue spans architecture or hard-to-reproduce failures |
| Advertising poster | A visual tool plus a creative brief | Typography, product fidelity or a complex composition fails |
Current OpenAI choices
OpenAI positions GPT-6.1 Sol for complex work at lower cost than Astra; Luna serves focused, efficient tasks. Sol medium is a reasonable editorial starting point for a substantial first draft. Raise effort or use Astra when the additional scrutiny improves the decision. This is a starting policy, not a comparative benchmark.
For API image generation, OpenAI currently positions GPT Image 2.5 Flare for speed and Sunburst for demanding quality. Those API names do not imply a selectable ChatGPT app setting.
Before doing this task, identify the main quality risk: factual grounding, reasoning, visual fidelity or implementation correctness. Use the available tools suited to that risk. Tell me which part requires review rather than promising a perfect result.
Current Claude settings
Claude exposes model and effort controls, with availability depending on the account. Anthropic recommends defaults for everyday work and more effort for complex analysis or coding. In a coding workflow, its current guidance suggests trying extra high effort for complex agent tasks on supported models before max.
Avoid paying for a higher setting to compensate for missing context. Run the same representative task with the same inputs and compare errors, time and the amount of editing you need.
- Writing: compare preservation of meaning and brand voice.
- Reports: compare citation accuracy and treatment of uncertainty.
- Posters: compare legibility and adherence to the brief.
- Code: compare working behaviour and regression risk.
Claude's current model families
Anthropic's current lineup positions Haiku 5.5 for high-volume, quick tasks, Sonnet 5.5 for a balance of speed and capability, Opus 5.5 for substantial coding and knowledge work, and Fable 5.1 for demanding reasoning and long tasks. Its platform guidance suggests Opus 5.5 as a capable starting point. Choose among the models actually available in your account and test a lower-cost option when the task is routine.
Common questions
Is the most expensive AI model always best?
No. Tool suitability, source quality and a clear brief may matter more. Use stronger reasoning where it changes the quality of the result.
Which model should I use for an advertising poster?
Use a visual-generation or design workflow for the asset. A text model can develop the strategy and copy, but exact layout and typography may need a separate design pass.
Keep exploring
Sources and editorial note
Guidance checked 9 October 2026. These AI-assisted guides and original templates are reviewed against the linked sources. Results depend on your inputs and available tools. Model recommendations are editorial starting points, not comparative test results.