Compare Computer-use models
AskUI vs computer use
Computer use is a model skill: read a screenshot, pick the next action. AskUI is the test system around it, and runs on these models.
Computer use · Claude, GPT, Gemini
What it is.
Anthropic, OpenAI and Google offer models that can operate a computer: they read a screenshot and choose the next click or keystroke. This is a model skill, offered through each provider's API. It is not a test tool, and AskUI uses these models.
Where computer use is strong
- Frontier models read almost any user interface from a screenshot.
- A quick start: a prototype clicks through a screen in an afternoon.
- Each new model generation improves every step.
Who does what
One step is a model call.
A test is dozens of them.
The model provides the eyes and the judgement. Everything around it comes from AskUI.
01 · Observe
AgentOS captures the screen
A screenshot of the device under test: desktop, phone, head unit or HMI.
AskUI
02 · Decide
The model picks the action
It reads the screenshot, the step text and the test so far, and chooses a tool call.
The model
03 · Act
AskUI carries it out
Click, type, scroll, or a tool such as SQL, HTTP or one you wrote.
AskUI
04 · Record
The step lands in the report
The step, its screenshot and the agent's reasoning, stored in your project.
AskUI
Models
Your model.
Your infrastructure.
Recommendations of the AskUI AI team, October 2026. Model generations change quickly.
- Recommended
- Claude 5.5 family. Sonnet 5.5 as the default, Haiku 5.5 for simple, stable flows, Opus 5.5 for the hardest UIs.
- Also supported
- GPT-6 family if Claude is not an option. Gemini 3.8 Flash for fast, low-cost runs.
- Self-hosted
- 27B to 35B open-weight vision models such as Qwen 3.8 or Meta Muse Glimmer, served with llama.cpp. Good for shorter, clearly guided tests.
- A model must have
- Vision, tool calling and a long context window: 200k tokens recommended, 128k for simpler tests.
- Where it runs
- AskUI Inference, your own cloud tenancy (Anthropic, Azure AI Foundry, a corporate gateway), or on-premise and air-gapped.
- Full detail
- Deployment, hardware sizing, security and model evaluation in the AI Models and Inference Guide (PDF). Setup in the docs: model providers.
Side by side
How they work.
Not a race between models. AskUI runs on the same models.
| Question | A computer-use model on its ownClaude, GPT, Gemini | AskUIOn the model you choose |
|---|---|---|
| How a test finds the UI | The model reads the screenshot and picks the next action. | The model you choose reads the screen. AskUI adds device access, rules, memory and checks around every step. |
| How tests are written | A prompt per task. | Plain language. Your manual test cases, often written from requirements. |
| Surfaces | Whatever machine you connect to the model's input and screenshot interface. | Desktop and remote computers, web browsers, Android emulators and phones, iOS simulators, several computers in one test, and embedded screens with no DOM. |
| Access needed to the app | An input and screenshot interface. Connecting the real device is your work. | None. No source code, instrumentation or accessibility tree. AgentOS gives the agent screen, keyboard and mouse. |
| When the screen is not as expected | The model plans each step itself. Catching loops, drift and false passes is yours to build. | The agent decides each next action from the screen. It closes unexpected pop-ups and corrects its own misclicks. Two attempts per step; In-Flight Guidance stops runs that loop; Dreaming proposes fixes for review. |
| End to end across systems | Whatever machines and systems your harness connects. | One test can drive several computers and check APIs and databases in between, with one report. Combining desktop, Android and web in one run is on the roadmap: profiles connect today. |
| Integrations beyond the UI | Tool calls you define, host and secure yourself. | Tool Store: SQL over ODBC, HTTP, shell and file checks, off until enabled. Custom C# tools and MCP servers, for example Vector CANoe or dSPACE, called from plain-language steps. |
| Where it runs | The provider's cloud, or wherever you host the model. | Your machines and your CI. On-premise and air-gapped, with your own model. |
| Test format | Prompts and the code of your own harness. | Markdown, CSV or JSON files in your own Git repository. |
| Evidence per run | The answer the model gives. Reports are yours to build. | A verdict, the expected and actual result and a screenshot for every step, plus the agent's reasoning. |
| Role of AI | The model is the whole product. | The engine, on the model you choose: Claude, GPT, Gemini or a self-hosted model. |
Describes a model used through its provider's API, checked October 2026. Provider features change; check each provider's documentation. Claude, GPT and Gemini are trademarks of their owners.
Which one fits
Both are good at something.
Choose computer use when
You need a one-off task or a prototype, or your team wants to build and own the harness itself.
Choose AskUI when
Tests must run every night on real devices, with defined verdicts and evidence an auditor accepts, inside your network.
Questions
- Is AskUI a computer-use model?
- No. AskUI is model-agnostic. Any model that understands screenshots and supports tool calling can drive the agent. Tests, prompts and reports stay the same when you switch models.
- Which model do you recommend?
- Claude Sonnet 5.5 as the default. Haiku 5.5 or Gemini 3.8 Flash for simple, stable flows. Opus 5.5 for the hardest UIs. If Claude is not an option, the GPT-6 family.
- Can we use our own model contract, for example Azure AI Foundry or a corporate LLM gateway?
- Yes. AskUI connects to any Anthropic-compatible or OpenAI-compatible endpoint, including gateways behind Microsoft Entra ID. You pay your provider directly, and AskUI charges no inference fee.
- Will a better model make AskUI unnecessary?
- A better model makes each step better. The test still needs devices, test cases, defined verdicts, evidence, memory and security. When a better model comes out, you switch to it in the settings and your tests stay the same.
- Why not build it ourselves on a computer-use API?
- You can. A model clicks through a screen in an afternoon. The harness, device access, verdicts, reports, secrets and CI take much longer to build and to keep running. Choose to build when you have a team to own that system.
- What data goes to the model?
- Per step, only the current screenshot, the step text and the conversation of the current test. Reports, screenshots, logs and secrets stay on your machines. With a self-hosted model, nothing leaves your network.
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