Prompts Engineering

Gemini 4 Argon Migration Guide: Parameter Changes and Best Practices

Prompt Edit here before copy/try — source content is unchanged

### Gemini 4 Argon Migration Guide

#### Key Changes
1. **Temperature Parameter Adjustments**
   - `temperature=0` is ignored. Use `response_schema` to control output format and `thinking_level` to control reasoning depth.
   - `thinking_budget` is replaced by `thinking_level` with options `low`, `medium`, `high`, default is `medium`.

2. **Removed Parameters**
   - `frequency_penalty`, `presence_penalty`, `candidate_count` have been removed. Using these will return a 400 error.

3. **Context Caching**
   - Explicit caching is removed. Implicit caching starts at 4,096 tokens on AI Studio and 6,144 on Vertex.
   - It's recommended to place static content at the beginning of the prompt and add a timestamp near the top to avoid caching issues.

4. **Model Turns**
   - Prefilled model turns are not supported and history cannot end with a model turn. If the model needs to start the reply, use `response_schema`.

#### Migration Recommendations
- **Prompt Layout**
  1. System instruction (role, rules, format)
  2. Tool list (same order every call)
  3. Few-shot examples
  4. Retrieved documents/conversation context (per session)
  5. User request, date, IDs (per call)

- **Cache Check**
  Add a timestamp near the top of the prompt and run the same call twice, then check `cached_content_token_count` in `usage_metadata`. If the second call returns 0, it means something above your static block is changing.

- **Migration Notes**
  If you were using `temperature=0` to control output, evaluate whether `response_schema` can fully replace its function. If your agent loop prefilled model turns, you need to reconsider that logic.

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temperature thinking_level response_schema tools examples context

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Usage & requirements

Adjust prompt parameters and layout according to the guide to adapt to the new features of Gemini 4 Argon

Tools: gemini google ai studio vertex
Variables: temperature thinking_level response_schema tools examples context
Source: r/PromptEngineering ↗

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