Treat prompt compatibility as part of the test
A prompt written around one model's habits can produce a different shape of answer from another. Begin with the same instructions so you can see that difference. Specify the required output format and the facts that must survive the transformation.
For a document rewrite, preserve names, dates and qualifications while changing tone. For a structured handoff, require the same keys and explicit missing-value behavior. Score those obligations before judging which prose you prefer.
Use a handoff with competing constraints
Try converting an incident note into a short status update. Include a confirmed fact, an unresolved hypothesis and an owner who has not yet responded. Ask for a fixed format that distinguishes confirmed information from what still needs checking.
A response fails if it turns the hypothesis into a fact or reports the silent owner's work as completed. This makes the comparison about evidence handling and instruction compliance rather than confidence of tone.
- Unconfirmed causes stay explicitly unconfirmed.
- The requested fields are present with no extra wrapper.
- Names and timestamps remain unchanged.
- No tool access or investigation is claimed without evidence.
Reasoning labels need their own record
The workspace exposes only effort choices verified for its connection. Save those choices with the result. Default settings can differ between models, and a matching label does not guarantee matching compute or token usage.
The official OpenAI reference for Sol also distinguishes ordinary text responses from tool-enabled workflows. This site compares text responses; it does not claim to test the model's full tool or computer-use capability.
Keep public context and hidden reasoning separate
In Chat, switching models preserves the visible conversation context. Hidden reasoning from an earlier model is not portable conversation text. A confirmed summary can shorten the public context, but it is a separate request with its own usage.
For a cleaner one-shot comparison, place all necessary facts in the shared task input. If you later revise the prompt to improve a failing model, save a new comparison. That preserves the distinction between a model change and a prompt change.
Review quality before comparing spending
Only a completed answer can be judged against the full requirement. Mark truncated outputs separately and keep unreviewed rows out of the acceptance denominator. Then compare known API costs and the recorded site credit charge without treating a pending bill as free.
The outcome is your evidence for this workflow. Neither manufacturer claims nor a public benchmark score are inserted as a verdict on your private inputs.
Manufacturer sources
- Claude Haiku 5.5 model reference · Checked 2026-10-09
- Anthropic API pricing · Checked 2026-10-09
- OpenAI model reference and pricing · Checked 2026-10-09
These sources describe the manufacturers' products. This page does not publish a site benchmark or reproduce a third-party ranking. Your saved outputs are private observations of your own inputs and settings.