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Gemini 3 Pro & Flash: Google's Frontier AI Models Explained

By Learnia Team

Gemini 3 Pro & Flash: Google's Frontier AI Models Explained

This article is written in English. Our training modules are available in French.

Google's Gemini 3 family, released in December 2025, introduces a powerful duo: Gemini 3 Pro for maximum capability and Gemini 3 Flash for speed and efficiency. Together, they offer flexibility for virtually any AI use case.


Gemini 3 Pro: Maximum Capability

Gemini 3 Pro is Google's flagship model, designed for the most demanding tasks:

Performance Highlights

  • PhD-level reasoning: Achieves ~90% on GPQA Diamond
  • Mathematical excellence: 100% on AIME 2025 high school math
  • Strong agentic performance: 76.2% on SWE-bench Verified
  • Massive context: 1,048,576 token window (over 1 million tokens)

Best For

  • Complex research and analysis
  • Multi-step mathematical reasoning
  • Long-document processing
  • Enterprise-grade applications

Gemini 3 Flash: Speed Meets Intelligence

Gemini 3 Flash breaks the traditional speed/intelligence trade-off:

Key Advantages

  • 3x faster than Gemini 2.5 Pro
  • 30% fewer tokens on average workloads = significant cost savings
  • Pro-grade reasoning with Flash-level latency
  • 78% on SWE-bench Verified — actually outperforms Pro in agentic coding!

The Sweet Spot

Gemini 3 Pro:

  • Speed: Baseline
  • Cost: Higher
  • SWE-bench: 76.2%
  • Reasoning: Maximum

Gemini 3 Flash:

  • Speed: 3x faster
  • Cost: ~30% cheaper
  • SWE-bench: 78% (higher!)
  • Reasoning: Near-Pro

The Thinking Level Parameter

Both Gemini 3 models introduce a game-changing feature: Thinking Level control.

Four Levels

  1. Minimal: Quick responses, lowest latency
  2. Low: Light reasoning, good balance
  3. Medium: Standard deep thinking
  4. High: Maximum reasoning depth

This lets you explicitly trade off between:

  • Response quality
  • Reasoning complexity
  • Latency
  • Cost

Example Usage

Quick question → Minimal thinking:

"What's the capital of France?" → Instant response

Complex analysis → High thinking:

"Analyze the market positioning of these 5 competitors..." → Deep reasoning


Multimodal Excellence

Gemini 3 models process multiple input types natively:

Supported Inputs

  • Text: Traditional prompts and documents
  • Images: Photos, diagrams, screenshots
  • Audio: Voice recordings, podcasts
  • Video: Clips and recordings
  • PDF: Documents with text and visuals combined

Multimodal Function Responses

A unique capability: function responses can now include objects like images and PDFs, not just text.


Where to Access Gemini 3

For Developers

  • Google AI Studio
  • Gemini CLI
  • Google Antigravity (new agentic IDE)
  • Android Studio
  • Vertex AI

For Consumers

  • Gemini app (available in "Fast" and "Thinking" modes)
  • AI Mode in Google Search

For Enterprise

  • Vertex AI
  • Gemini Enterprise

Choosing Between Pro and Flash

Use Gemini 3 Pro When:

  • Working with maximum context lengths (1M+ tokens)
  • Performing cutting-edge research
  • Quality is paramount regardless of cost
  • Tasks require deepest possible reasoning

Use Gemini 3 Flash When:

  • Building production applications
  • Speed and cost efficiency matter
  • Agentic coding workloads (it actually performs better!)
  • Iterative development requiring fast feedback
  • High-frequency request handling

Key Takeaways

  1. Gemini 3 Flash often rivals Pro while being 3x faster and 30% cheaper
  2. The Thinking Level parameter gives explicit control over reasoning depth
  3. 1M+ context window handles massive documents
  4. Both models excel at multimodal understanding
  5. Flash surprisingly outperforms Pro on agentic coding

Master Output Control and Format Engineering

Getting the most from Gemini 3's flexibility requires understanding how to control and format AI outputs precisely—from JSON structures to multi-format responses.

In our Module 2 — Output Control & Formatting, you'll learn:

  • Structured output formats (JSON, XML, Markdown)
  • Token optimization for cost savings
  • Multi-format response engineering
  • Handling multimodal inputs and outputs
  • Output validation and post-processing

Explore Module 2: Output Control & Formatting

GO DEEPER

Module 2 — Structured Outputs

Learn to get reliable, formatted responses like JSON and tables.