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+# Deep Dive #2: Supported AI Models in ABP Studio + Usage Recommendations
+
+There is one question I ask almost as often as "Which mode should I use?":
+
+**Which model should do this work?**
+
+At first, it is tempting to answer that question by always choosing the strongest model in the list. That feels safe. If a model is more capable, why not use it for everything?
+
+In real work, I do not think about it that way.
+
+When I use **ABP Studio AI**, the model choice is part of the workflow. Some tasks need careful reasoning. Some need speed. Some need a large context window. Some need image support because the browser or a screenshot is involved. Some are small text-processing tasks where using the most capable model would only make the work slower and more expensive.
+
+So I treat model selection as a practical decision, not a trophy selection.
+
+## What ABP Studio Supports Today
+
+ABP Studio uses an OpenRouter-backed model setup by default. That gives Studio a unified way to work with different model providers while keeping the model list focused on models that make sense for an AI coding agent.
+
+The important word here is **focused**.
+
+OpenRouter may know about many models, but ABP Studio does not simply expose every model as an equally good choice for agent work. A coding agent needs things like a useful context window, tool support, text output, and reliable behavior in repeated agent loops. Studio keeps the model experience closer to that reality.
+
+The built-in model set currently includes:
+
+| Model | How I think about it |
+| --- | --- |
+| Claude Sonnet 4.6 | The default main model for day-to-day Ask, Plan, and Agent work. |
+| Claude Haiku 4.5 | A fast supporting model for research, browser work, and lightweight text processing. |
+| Claude Opus 4.7 | A stronger option when the task needs deeper reasoning or more careful review. |
+| GPT-5.5 | Another strong option for main conversations or review-style work. |
+| GLM-5.1 | A text/code option for tasks that do not need image input. |
+
+I do not read this list as a ranking. I read it as a toolbox.
+
+## The Main Model
+
+The main model is the one I feel most directly in the conversation.
+
+It is used when I ask questions, create plans, or let ABP Agent work through an implementation. This is the model behind the normal flow of the chat.
+
+![ABP Agent model selector showing the current conversation model](abp-agent-model-selector.png)
+
+For most work, I keep a balanced model as the main model. A Sonnet-style model is a good default because it is capable enough for real development tasks without making every small question feel heavy.
+
+This is the model I use for:
+
+* Understanding a module or package
+* Planning a feature before editing code
+* Applying a reviewed plan
+* Fixing ordinary build or test failures
+* Making changes where the expected result is easy to review
+
+When the task gets broader, I become more intentional.
+
+If I am asking ABP Agent to reason across several modules, plan a risky refactor, review architecture, or inspect a subtle regression, I am more willing to switch to a stronger model. The extra capability is useful when the cost of a shallow answer is high.
+
+For a quick localization change or a small DTO update, that same choice can be wasteful. The strongest model is not always the best model for the moment.
+
+## Role-Based Models
+
+One detail I like in ABP Studio AI is that model selection is not only one global dropdown.
+
+Studio separates the main conversation model from supporting model roles. That means I can keep the main model strong enough for the conversation while using lighter models for background work.
+
+![ABP Agent model settings for main, research, browser, and text processor models](abp-agent-model-settings-agents.png)
+
+The roles are easier to understand if I describe them by how they feel in daily use.
+
+**Main Model** is the model I am actively talking to. It carries the normal Ask, Plan, and Agent experience.
+
+**Research Model** is for research and ABP documentation searcher work. I usually keep this lightweight because research often involves gathering, narrowing, and summarizing context before the main model decides what to do with it.
+
+**Browser Model** is used by the browser subagent in Agent mode. This role should stay fast and practical. When browser screenshots are involved, I choose a model that supports image input. A text-only model may be fine for code, but it is not the right fit when the work depends on seeing the UI.
+
+**Text Processor Model** is for smaller language tasks such as summarizing errors, generating commit messages, or consolidating learned lessons. This is exactly where I do not want to spend the most capable model every time.
+
+The Git Review model is separate too.
+
+![ABP Agent model settings for Git Review model selection](abp-agent-model-settings-git-review.png)
+
+For Git AI Review, I like the "Ask me every time" behavior. Some reviews are routine. Some reviews deserve a stronger model because the change is large, security-sensitive, or touches architecture. Asking each time keeps that decision close to the actual change.
+
+If a team wants consistent review behavior, a fixed review model also makes sense. The key is that Git Review does not have to silently follow the same model I use for ordinary chat.
+
+## How I Choose In Practice
+
+For quick questions, I use the default main model.
+
+If I am asking "Where is this permission defined?" or "Why does this module reference that package?", I do not need to overthink the model. I want a clear answer and maybe a few source references.
+
+For planning larger work, I use a stronger main model when the decision matters.
+
+Plan mode is where the model can save me from an expensive wrong turn. If the change crosses layers, modules, permissions, UI, or database behavior, I prefer a model that can hold more context and reason carefully. I still narrow the scope where possible, because a focused prompt usually beats a huge unfocused one.
+
+For implementation, I care about reliability more than raw size.
+
+Agent mode is not only about generating code. It is about reading the solution, editing files, running checks, seeing failures, and trying again. A good main model should follow instructions consistently and use tools well. For supporting roles, I usually keep the lighter defaults.
+
+For UI and browser tasks, I check image support.
+
+If the task involves screenshots, browser interaction, visual verification, or UI state, the browser model needs to be able to understand images. This is one reason I do not treat every text/code model as interchangeable.
+
+For reviews, I choose based on risk.
+
+A small formatting or localization change does not need the same review setup as a large change in authorization, multi-tenancy, persistence, or distributed behavior. For deeper reviews, I am willing to use a stronger model because the goal is not speed. The goal is to catch what I missed.
+
+For cost and latency, I avoid using the strongest model everywhere.
+
+This is not only about credits. It is also about pace. If every background task uses a heavy model, the development loop feels slower. Keeping lightweight models for lightweight jobs makes ABP Studio AI feel more responsive.
+
+## A Simple Rule
+
+The model name matters less than the job.
+
+When I choose a model in ABP Studio AI, I usually ask:
+
+| Situation | Model choice I prefer |
+| --- | --- |
+| Normal Ask, Plan, or Agent work | Balanced main model |
+| Broad planning or risky implementation | Stronger main model |
+| Research and documentation lookup | Lightweight supporting model |
+| Browser tasks with screenshots | Vision-capable browser model |
+| Error summaries and commit messages | Lightweight text processor model |
+| Important Git AI Review | Stronger model or ask each time |
+
+That keeps the experience practical.
+
+Modes decide how much action I want: Ask, Plan, or Agent.
+
+Models decide which brain should handle the work.
+
+When those two choices are made intentionally, ABP Studio AI feels less like one generic AI button and more like a set of tools I can tune for the task in front of me.