How to Use Cherry Studio for Simultaneous Multi‑Model AI Calls

This guide shows how to install Cherry Studio, configure multiple AI model providers, and send a single prompt that triggers several models at once, with step‑by‑step screenshots, layout tips, and cost considerations for free and paid services.

Wuming AI
Wuming AI
Wuming AI
How to Use Cherry Studio for Simultaneous Multi‑Model AI Calls

Problem

When brainstorming with AI, a user often needs to send the same prompt to several different model endpoints because a single model may give inconsistent answers across questions. Manually opening each provider’s website and copying the prompt is inefficient.

Solution Overview

Use Cherry Studio, an open‑source desktop client that can invoke multiple LLM providers in parallel with a single prompt, then compare or combine the responses.

Installation

Download the installer from https://www.cherry-ai.com/download and run it.

Cherry Studio installer
Cherry Studio installer

Configure Model Providers

Open Settings (lower‑left corner) → Model Service.

Select a provider, e.g., SiliconFlow (https://cloud.siliconflow.cn/i/98WfcWmQ), click “Get key”, create or retrieve an API key, and paste it into the key field.

Click Manage to add the desired models. Domestic providers typically expose DeepSeek, Kimi, Qwen, etc.

Provider configuration
Provider configuration

Multi‑Model Invocation

Return to the chat window.

Press the @ button at the bottom and tick the models added in the previous step.

Enter the prompt; Cherry Studio sends it concurrently to all selected models and displays each response.

By default responses are stacked vertically. Click the layout icon to switch to horizontal arrangement for side‑by‑side comparison.

Model selection
Model selection
Responses vertical
Responses vertical
Horizontal layout
Horizontal layout

Cost Considerations

Cherry Studio itself is free and open‑source, shipping with two free models. Provider APIs are usually billed per token; typical usage costs are comparable to the price of one or two meals per month.

Best Practices

Rotate among multiple models to avoid “model echo chambers” and mitigate over‑reliance on a single provider.

Inspect responses side‑by‑side to select the most accurate answer or to synthesize a combined response.

Artificial IntelligenceAI toolsprompt engineeringmulti-modelCherry Studiomodel aggregation
Wuming AI
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