Gemini 3 Pro
Gemini 3 Pro is a multimodal text generation model from Google with a 1,000,000-token context window.
Google's flagship multimodal model with 1M context
Gemini 3 Pro is a flagship large language model developed by Google, released in November 2025 under the identifier gemini-3-pro-preview. It supports a context window of up to one million tokens, allowing it to process and reason over very large volumes of text and video content within a single session. The model is classified as multimodal and includes support for video analysis alongside standard text generation tasks.
Gemini 3 Pro is designed for use cases that require handling long documents, extended conversations, or large codebases without truncation. Its one-million-token context makes it well suited for tasks like document summarization, multi-document analysis, and long-form content generation. The model is available through Google's Gemini API and can be accessed on MindStudio without requiring separate API key configuration.
What Gemini 3 Pro supports
Large Context Window
Processes up to 1,000,000 tokens in a single request, enabling analysis of entire books, large codebases, or extended conversation histories without truncation.
Video Analysis
Accepts video as an input modality, allowing the model to interpret and reason over video content directly within a prompt.
Multimodal Input
Handles multiple input types beyond plain text as part of Google's multimodal model family, supporting richer and more varied prompts.
Long-Form Text Generation
Generates responses of up to 30,000 tokens, making it suitable for producing detailed reports, long-form articles, or extended code outputs.
Flagship Model Tier
Positioned as Google's top-tier Gemini release, intended for complex tasks that benefit from the full capacity of the model family.
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Get Started FreeBenchmark scores
Scores represent accuracy — the percentage of questions answered correctly on each test.
| Benchmark | What it tests | Score |
|---|---|---|
| MMLU-Pro | Expert knowledge across 14 academic disciplines | 89.8% |
| GPQA Diamond | PhD-level science questions (biology, physics, chemistry) | 90.8% |
| LiveCodeBench | Real-world coding tasks from recent competitions | 91.7% |
| HLE | Questions that challenge frontier models across many domains | 37.2% |
| SciCode | Scientific research coding and numerical methods | 56.1% |
| AIME 2025 | American math olympiad problems (2025) | 95.0% |
| ARC-AGI-2 | Novel abstract reasoning and pattern recognition | 31.1% |
| SWE-bench Verified | Real GitHub issues requiring multi-file code fixes | 76.2% |
| MMMLU | Multilingual and multimodal understanding | 91.8% |
Common questions about Gemini 3 Pro
What is the context window size for Gemini 3 Pro?
Gemini 3 Pro supports a context window of 1,000,000 tokens, which allows it to process very large documents, long conversations, or extensive codebases in a single request.
Does Gemini 3 Pro support video input?
Yes. The model metadata indicates that Gemini 3 Pro supports video analysis as an input modality, in addition to standard text-based prompts.
What is the maximum response size for Gemini 3 Pro?
The model has a maximum response size of 30,000 tokens per output, which supports detailed and lengthy generated content.
Is Gemini 3 Pro still available to use?
The model's current status is listed as deprecated. It was added to MindStudio in November 2025 under the identifier gemini-3-pro-preview. Availability may be subject to change based on Google's API offerings.
What is the pricing for Gemini 3 Pro on MindStudio?
Published pricing information is not available in the current metadata. You can use Gemini 3 Pro on MindStudio without needing to supply your own API key.
Who publishes Gemini 3 Pro?
Gemini 3 Pro is published by Google and provided as a first-party model through Google's Gemini API infrastructure.
What people think about Gemini 3 Pro
Community discussion around Gemini 3 Pro on Reddit has been broadly positive, with users highlighting its agentic capabilities and benchmark performance, including a noted result of completing Pokémon Crystal using 50% fewer tokens than its predecessor. The release of the related Gemini 3.1 Pro update generated significant engagement, with one thread accumulating over 2,400 upvotes and 528 comments.
Some threads focus on benchmark comparisons and token efficiency as practical indicators of model capability, while others discuss the Flash variant's cost and arena rankings as points of reference for the broader Gemini 3 family. Overall community interest centers on real-world agentic use cases and cost-performance tradeoffs.
Google releases Gemini 3.1 Pro with Benchmarks
Google just dropped Gemini 3.1 Pro. Mindblowing model.
Google just dropped a new Agentic Benchmark: Gemini 3 Pro beat Pokémon Crystal (defeating Red) using 50% fewer tokens than Gemini 2.5 Pro.
Google releases Gemini 3 Flash: Ranks #3 on LMArena (above Opus 4.5), scores 99.7% on AIME and costs $0.50/1M plus Benchmarks.
Parameters & options
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