No chat app contains every AI model. Labs release new versions, retire old ones, and limit certain capabilities by plan or region. Treat “all AI models in one app” as a search intent, then compare the catalog you can use today.
Compare model coverage by family and version
Start with the model families required by your work. A useful catalog may include GPT, Claude, Gemini, DeepSeek, and open-weight options, but the exact version matters. Check the model ID or version shown in the product instead of assuming that a familiar family name means the latest release.
Create a short table with these fields:
| Field | Question |
|---|---|
| Model | Which exact model or version is available? |
| Plan | Which subscription includes it? |
| Input | Does it accept text, images, or files? |
| Tools | Does it support web search, reasoning, or connected tools? |
| Processing | Where does the selected model process the request? |
Update the table when the catalog changes.
Read quotas before comparing subscription prices
Two apps can list the same model and offer different usable access. One plan may apply a shared message allowance. Another may limit a specific model, tool, context size, or research mode.
Check the limits for your normal workday:
- Messages or credits by model.
- File size, number of files, and storage limits.
- Web search, image generation, and research allowances.
- Context and output limits for longer tasks.
- Rate limits during busy or automated use.
Ask what happens when a limit is reached. A fallback model may be fine for a draft and unsuitable for a reviewed analysis.
Compare tools as part of the workflow
Model access alone does not finish a task. Test the product with a current web question, a PDF, an image, and a project that spans several conversations. Check whether citations open, files remain attached to the right project, and outputs can move into the format your team uses.
Tool availability can differ by model. Confirm the model and tool combination rather than checking two separate feature lists.
Test task fit with the same material
Select four representative tasks, such as a customer reply, a code change, a sourced research brief, and a document comparison. Give each model the same instructions and source material. Score the result for accuracy, editing time, source quality, and format compliance.
Use the model comparison tool and leaderboard to build a shortlist. Your own task set should make the final decision because benchmark strength does not measure every workflow.
Check processing differences
Processing location is always in the EU. Data centers in Germany and Finland. Review the product documentation and model information for each workload, and confirm the relevant retention and training terms before uploading business material.
Calculate subscription value
Count accepted work, not listed models. For one month, record how many tasks reached a usable result, how much editing they needed, and whether people required another paid product. Add seat count, plan limits, and administration time.
A multi-model subscription has value when it reduces account switching and gives people a suitable model and tool set for their recurring tasks. It has less value when the important models sit behind limits your team reaches each week.
Review the LLMBase AI chat, current plans, model comparison, and leaderboard with the same shortlist and test set.