Gemini 3 Pro Overview: Google’s Most Intelligent AI Model
On November 18, 2025, Google officially launched Gemini 3 Pro, its most advanced AI model to date. This model surpasses its predecessors across multiple dimensions, particularly excelling in reasoning capabilities, multimodal understanding, and code generation.
Great News — Global GPT has now integrated the Gemini 3, and you can also access the latest ChatGPT 5.1 through this all-in-one platform.
Gemini 3 Core Capabilities
- Deep Reasoning – Gemini 3 Pro features the innovative “Deep Think” functionality, enabling human-like deep thinking by evaluating multiple possibilities and checking its own logic before answering complex questions.
- Native Multimodal – The model is fundamentally designed to seamlessly understand and process text, images, audio, video, and code.
- Extended Context Window – Supports up to 1 million tokens of input context and 64,000 tokens of output, ideal for processing long documents and complex conversations.
- Agentic Workflows – Specially optimized for autonomous coding agents and complex zero-shot tasks. With the newly released Bash tools, it can navigate file systems and drive development processes.
- “Vibe Coding” – Supports generating complete applications from natural language descriptions without traditional programming syntax.
Gemini 3 Pro API Pricing
Google’s latest flagship model, Gemini 3 Pro, has launched its API preview with a clear and competitive pricing model. Compared to previous models, Gemini 3 Pro adopts a tiered pricing strategy based on context length, designed to optimize costs for large-scale projects and long-text processing. For contexts under 200,000 tokens, input/output prices are $2.00/$12.00 per million tokens; above 200,000 tokens, they increase to $4.00 and $18.00 respectively.
Core Pricing Overview (Per Million Tokens)
| Context Length | Input Price | Output Price |
| ≤ 200,000 Tokens | $2.00 | $12.00 |
| > 200,000 Tokens | $4.00 | $18.00 |
Gemini 3 Pro API Pricing Mechanism Explained
Gemini 3 Pro API pricing revolves around two key dimensions: token quantity and context window length.
- Core Billing Unit: Tokens
Like most large language models (LLMs), Gemini 3 Pro charges separately for input tokens and output tokens, measured per million tokens (per 1M tokens).
- Input Tokens (Input Price): The volume of data sent to the model—your prompts, documents, code, etc.
- Output Tokens (Output Price): The volume of responses, summaries, code, etc., generated by the model, including tokens used for “thinking.”
- Cost Tiers: The Importance of Context Windows
A standout feature of Gemini 3 Pro is its extremely long context window (up to 1 million tokens). To reflect the computational cost of processing ultra-long contexts, Google introduced tiered pricing:
| Context Length Range | Use Cases | Pricing Rate |
| Standard Context (≤ 200K Tokens) | Common chat, short summaries, standard tasks | Lower rate |
| Long Context (> 200K Tokens) | Legal document analysis, deep research, complex codebase understanding | Higher rate |
Long-context tasks have input/output prices that are double those of standard contexts, reflecting their high value in complex scenarios.
Cost Estimation Examples: How Developers Can Budget
Understanding real-world use case costs helps businesses and developers accurately plan budgets. Here are several cost estimates based on current preview pricing:
Example 1: Standard Customer Service Chatbot (Low Context)
Assumptions:
- Input: 5,000 Tokens
- Output: 1,000 Tokens
- Context: 5,000 Tokens (≤ 200K)
| Cost Type | Calculation | Cost (USD) |
| Input | 5,000 × $2.00 / 1M | 0.01 |
| Output | 1,000 × $12.00 / 1M | 0.012 |
| Single Request Total | =$0.022 |
Example 2: Document Analysis & Summarization (Medium-Long Context)
Assumptions:
- Input: 150,000 Tokens (analyzing a long report)
- Output: 8,000 Tokens (generating summary)
- Context: 150,000 Tokens (≤ 200K)
| Cost Type | Calculation | Cost (USD) |
| Input | 150,000 × $2.00 / 1M | 0.3 |
| Output | 8,000 × $12.00 / 1M | 0.096 |
| Single Request Total | =$0.4 |
Example 3: Deep Research Task (Ultra-Long Context)
Assumptions:
- Input: 350,000 Tokens (analyzing multiple documents)
- Output: 15,000 Tokens (generating detailed report)
- Context: 350,000 Tokens (> 200K, higher rate applies)
| Cost Type | Calculation | Cost (USD) |
| Input | 350,000 × $4.00 / 1M | 1.4 |
| Output | 15,000 × $18.00 / 1M | 0.27 |
| Single Request Total | =$1.67 |
Gemini 3 Free Tier
You can try the model for free in Google AI Studio, but currently, there is no free tier available for gemini-3-pro-preview in the Gemini API.
