Free Tools · GPT-5.6 selector

Match the model to the work.

Answer seven plain questions. Get a workload-fit recommendation, a benchmark-informed value alternative, and a stronger option.

Step 1 · Describe the task

Choose the answer that best describes the task, not the answer that feels safest.

1How repeatable is the task?

Would a clear checklist work most of the time?

2How much judgment does the task require?

Is the main challenge execution, synthesis, or deciding between tradeoffs?

3What happens if the answer is wrong?

Think about stakes and how easily a person can reverse the result.

4How many sources, constraints, or steps are involved?

Count competing inputs, requirements, and dependencies.

5How easy is it to verify the result?

Can a person quickly tell whether it is good enough?

6What matters most for this run?

Volume and speed can justify a lighter option when the work is clear.

7Is this the final critical review?

Reserve this for a difficult final pass where a small reliability gain matters.

Benchmark context

Cost changes the answer.

Workload fit comes first. The benchmark adds a second lens: some smaller-model, higher-effort combinations can deliver compelling intelligence per dollar.

Artificial Analysis chart comparing GPT-5.6 Sol, Terra, Luna, and GPT-5.5 intelligence index against weighted cost per benchmark task.
Source: Artificial Analysis Intelligence Index. Cost is the weighted average per Artificial Analysis benchmark task, not OpenAI pricing or a guarantee for real Codex workflows.
Advanced choices beyond the selector

Light, Medium, High, and Extra High tune the selected model. Use the lowest effort that produces the result you need. The selector reserves Light for tightly bounded Luna work and Extra High for unusually difficult or final reviews.

Max and Ultra solve different problems. Max gives one model more time for the hardest single task. Ultra brings in subagents for work that divides into meaningful parallel lanes. Most tasks need neither.

Sources

Guidance and benchmark evidence

OpenAI guidance determines workload fit. The third-party benchmark informs value alternatives. Test important workflows with representative work.

Choose for task fit first, then compare the value alternative. Escalate when ambiguity or the cost of being wrong outweighs the extra usage. · A free tool from Majestic Labs.

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