Get more careful answers

Toskar has four ways to give a question more care: Effort in the chat, a reasoning model, a profile's Reasoning level, and comparing independent drafts. Each makes answers slower, and some need more memory, so save them for questions that need it, such as math, logic, plans with several steps, and questions about your data.

Effort, in the chat's options, sets how much work goes into an answer. Fast answers in one go, on a model that's already loaded. Balanced plans requests with several parts, reads a page for each look-up, and corrects figures once. Thorough reads more pages, checks figures twice, and uses the largest model that fits, even for a quick question. Auto keeps quick questions fast and gives questions about your data, and requests with several parts, more care. Your choice is remembered. When an answer missed something, ask again with Thorough.

Some models think before they answer: they work through the problem first, then write the answer. Models marks them Reasoning, and Recommended suggests one as Best for careful reasoning. They do better at math, logic, and puzzles, and take longer to start answering. Model Auto doesn't pick one, even at Thorough, unless no other installed model fits, so a quick question never waits on one. To use one, choose it in the chat's model menu; the chat keeps it until you choose another.

While a reasoning model thinks, the chat says Reasoning… with how long it has taken, on the web and in the Toskar app. Under the answer, What I did says how long it thought, and Thinking opens what it thought, folded away until you want it.

A profile's Reasoning level is the effort its chats use when Effort is left on Auto. Set it to Thorough on a profile you use for careful work, such as Research, and its chats get that care without choosing it each time. It's under Orchestration, in the profile's Strategy and computers tab in Profiles & Orchestration.

When one draft isn't enough, a profile can draft each answer three times, independently, and compare them before you see one. See Compare independent drafts. It catches slips a single draft makes, such as a wrong step in a word problem, and takes longer and uses more of your computers.

More care costs time and memory. Thorough and larger models take longer to load and to answer, a reasoning model writes its thinking before the answer, and compared drafts run three times. A larger model needs more memory, and a reasoning model's thinking takes room in its context window while it answers.