Debug a React error
Coding lane
Reasoning-focused model
Project files and code context
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Auto model selector
Auto reads the job, chooses an eligible model lane, adds tools like search or image understanding when they matter, and keeps the work inside one AI workspace.
Auto does not claim one model is universally best.
Auto should explain meaningful routing choices when the task is complex.
Auto routes within the models, tools, and credits available to the workspace.
Debug a React error
Reasoning-focused model
Project files and code context
Research a current market
Search-ready model
Web search and source review
Rewrite a proposal
Clear drafting model
Tone and structure controls
Analyze a screenshot
Image-capable model
Image understanding
Routing signals
Model comparison still matters, but the first SEO truth is the product behavior: Tryall decides what kind of AI response the task needs before asking users to think about provider names.
Auto separates coding, research, writing, analysis, image, and routine assistant work before choosing a lane.
The biggest model is not always the right model. Auto keeps simple work efficient when quality does not need a frontier lane.
When the answer depends on recent facts, Auto can route toward search-enabled behavior instead of relying only on model memory.
Routing respects available model lanes and credits, so the choice fits the user's actual workspace.
Use cases
Coding
Use Auto for debugging, implementation plans, refactors, and code explanations when you do not want to pick a model first.
Choose a coding laneResearch
Ask for market context, vendor comparisons, source-backed summaries, and fast orientation on unfamiliar topics.
Writing
Draft, rewrite, summarize, and shape documents while Auto keeps routine language work out of oversized model lanes.
Image analysis
Upload screenshots, UI captures, diagrams, or visual references and let Auto choose an image-capable path.