Large-codebase reasoning
Analyze repositories, plan multi-file changes, debug difficult behavior, and coordinate tool-based implementation work.
Independent tool overview
Gemini 3.1 Pro at a glance
Gemini 3.1 Pro is Google's advanced reasoning model for complex coding, research, analysis, and agentic workflows, with multimodal inputs and a one-million-token context window.
Visit the official Gemini 3.1 Pro site ↗
- Model ID
- gemini-3.1-pro-preview
- Status
- Preview
- Input context
- 1,048,576 tokens
- Maximum output
- 65,536 tokens
- Inputs
- Text, image, video, audio, and PDF
- Output
- Text
- Knowledge cutoff
- January 2025, with grounding tools available
- Last reviewed
- August 29, 2026
Overview
What Gemini 3.1 Pro is
Gemini 3.1 Pro is the reasoning-focused model in Google's Gemini 3 family. It is intended for work where a fast answer is less important than following a long chain of requirements, combining information from several sources, using tools, or reasoning across a large codebase or document set.
The API accepts text, images, video, audio, and PDFs and returns text. It supports function calling, structured output, code execution, context caching, Google Search grounding, URL context, Google Maps grounding, and adjustable thinking levels. Google also exposes a custom-tools endpoint for agentic coding workflows that mix shell commands with developer-defined tools.
Consumers can use 3.1 Pro in the Gemini app and NotebookLM, while developers can access the preview model through Google AI Studio, the Gemini API, Vertex AI, Gemini CLI, Android Studio, and Antigravity. The API endpoint remains a preview model, so production systems should isolate it behind versioned configuration and regression tests.
Use cases
Who Gemini 3.1 Pro is best for
The strongest fit depends on the job you need the product to complete, not the size of its feature list.
Complex research synthesis
Combine long documents, URLs, search results, tables, and multimodal evidence into a structured analysis.
Agentic workflows
Use function calling, structured outputs, code execution, and custom tools for reliable multi-step tasks.
Multimodal document analysis
Reason across PDFs, images, recorded audio, and video when the answer depends on more than plain text.
Hard planning problems
Work through long requirement sets, tradeoffs, constraints, and dependencies before producing a decision or implementation plan.
Capabilities
Core Gemini 3.1 Pro features
One-million-token context
Process large codebases, document collections, long recordings, or extended conversations in a single request when the application supplies the relevant material.
Adjustable thinking
Choose low, medium, or high thinking levels to balance latency and reasoning depth; high is the default for 3.1 Pro.
Multimodal understanding
Accept text, images, video, audio, and PDF inputs while producing text responses for analysis and downstream automation.
Grounding and context tools
Use Google Search, Google Maps, URLs, file search in AI Studio, and code execution to bring external or computed evidence into a response.
Function calling and structured output
Connect business actions and developer tools, then constrain responses to a defined schema for more reliable automation.
Custom-tools endpoint
Use gemini-3.1-pro-preview-customtools when an agent must prioritize shell and developer-defined tools, with the tradeoff that quality may fluctuate outside those workflows.
Process
How the Gemini 3.1 Pro workflow works
Step 1
Choose the right access surface
Use the Gemini app or NotebookLM for interactive work, AI Studio for prototyping, and the Gemini API or Vertex AI for a production integration.
Step 2
Define the output contract
State the goal, constraints, audience, acceptable sources, and required structure; use a schema when another system will consume the answer.
Step 3
Supply only relevant context
A large context window is capacity, not a requirement. Curate files and sections so cost and attention are spent on evidence that affects the result.
Step 4
Select tools and thinking level
Enable search, URLs, code execution, or functions only where needed, and lower thinking depth for routine requests that do not justify Pro-level latency and cost.
Step 5
Validate important outputs
Check citations, calculations, code, tool arguments, and factual claims before acting, especially when the model is allowed to change external systems.
Step 6
Control cost and model drift
Use context caching or Batch/Flex options where appropriate, log token usage, pin the endpoint, and rerun evaluation cases before adopting a new preview revision.
Cost
Gemini 3.1 Pro pricing and free plan
Gemini 3.1 Pro has consumer subscription access and usage-based developer pricing. API rates increase when a prompt exceeds 200,000 tokens. Consumer availability and quotas are compute-based and vary by prompt complexity, features, conversation length, plan, and region.
Gemini Free
$0
Personal Gemini access with varying availability for 3.1 Pro.
- Limited and compute-based 3.1 Pro access
- 15GB Google storage
- Gemini app
- Deep Research and multimodal features with limits
Google AI Pro
$19.99/month
Higher consumer access to Google's Pro models and productivity features.
- 4x Free usage access in the Gemini app
- 5TB Google storage
- Gemini in Gmail, Docs, Vids, and more
- Expanded Notebook and Flow access
Google AI Ultra 5x
$99.99/month
Premium personal plan with five times the Pro usage limits.
- Higher access to 3.1 Pro
- Advanced feature access
- 10,000 Flow credits
- Cloud storage starting at 20TB
Google AI Ultra 20x
$199.99/month
Highest listed personal usage tier.
- 20x Pro usage limits
- Highest access to Pro models
- 25,000 Flow credits
- Priority access to advanced features
Gemini API — prompts up to 200K
$2 input / $12 output per 1M tokens
Standard API pricing for shorter contexts.
- Text, image, and video input use the listed token rate
- Thinking tokens count toward usage
- Caching and alternate consumption options supported
- AI Studio prototyping available
Gemini API — prompts over 200K
$4 input / $18 output per 1M tokens
Higher rate applied to requests with large input contexts.
- Applies above 200,000 input tokens
- Large-context output is billed at the higher output rate
- Monitor repeated conversation history
- Consider caching and retrieval before sending full corpora
Vertex AI / Enterprise
Usage-based or contracted
Google Cloud access with enterprise deployment, governance, and billing options.
- Preview model in Model Garden
- Enterprise security and administration
- Regional availability and quotas apply
- Cloud pricing and terms may differ from the Gemini Developer API
Pricing checked . Check current pricing at the source ↗
Assessment
Gemini 3.1 Pro strengths and limitations
Where it stands out
- Strong fit for difficult reasoning, coding, research, and multi-step tool use
- One-million-token context can accommodate large repositories and document sets
- Native multimodal input reduces the need for separate transcription and extraction pipelines
- Broad tool support includes search grounding, URLs, Maps, code execution, function calling, and structured output
- Available across consumer, developer, coding, and enterprise Google products
What to consider
- The API model is still in preview, so behavior, quotas, endpoints, and availability can change before general availability
- It returns text rather than generating images or audio and does not support the Gemini Live API
- Requests above 200,000 input tokens move into a more expensive pricing tier
- High thinking can increase time to first answer and total billed output tokens
- The large context window does not guarantee that every supplied detail will receive equal attention
- Grounding reduces but does not eliminate factual errors; citations and tool results still require verification
- Consumer usage limits are compute-based rather than a guaranteed fixed number of prompts
Compare
Gemini 3.1 Pro alternatives
The right alternative depends on the specific output, workflow, controls and budget your project requires.
Business Operations
ChatGPT
Choose ChatGPT for OpenAI's broad consumer ecosystem, custom tools, multimodal creation, and integrated agent experiences.
Explore ChatGPT →Project Management
Claude
Choose Claude for Anthropic's long-context writing, coding, analysis, and agent workflows, especially if you prefer its product ecosystem.
Explore Claude →Business Operations
DeepSeek
Choose DeepSeek when open-model availability and lower-cost reasoning options are more important than Google's integrated tools and multimodal stack.
Explore DeepSeek →Questions
Gemini 3.1 Pro FAQs
What is Gemini 3.1 Pro best used for?
It is designed for complex reasoning, software engineering, research synthesis, multimodal analysis, and agentic workflows that require reliable tool use across multiple steps.
Is Gemini 3.1 Pro generally available?
No. The Gemini API endpoint is still named gemini-3.1-pro-preview, and Google lists all Gemini 3 API models as preview. No shutdown date has been announced for this endpoint.
How large is the Gemini 3.1 Pro context window?
The model supports up to 1,048,576 input tokens and 65,536 output tokens. Sending more than 200,000 input tokens uses the higher API price tier.
Can Gemini 3.1 Pro analyze video and audio?
Yes. It accepts video and audio alongside text, images, and PDFs. Its output is text; audio generation, image generation, and the Live API are not supported by this model.
How much does the Gemini 3.1 Pro API cost?
For prompts up to 200,000 tokens, Google lists $2 per million input tokens and $12 per million output tokens. Above 200,000 input tokens, rates rise to $4 input and $18 output per million tokens.
Can I use Gemini 3.1 Pro for free?
The Gemini app includes varying free access to 3.1 Pro. API prototyping may also have free allowances in Google AI Studio, but availability, limits, and supported features can differ from paid API access.
What is the custom-tools endpoint?
gemini-3.1-pro-preview-customtools is a separate API endpoint optimized to prioritize shell commands and developer-defined tools in agentic workflows. Google notes that quality may fluctuate on tasks that do not benefit from those tools.
Bottom line
Our Gemini 3.1 Pro verdict
Gemini 3.1 Pro is a compelling choice when a job combines long context, multimodal evidence, difficult reasoning, and tools. It is overkill for simple chat or high-volume classification, where a current Flash model will usually be faster and cheaper. For production agents, the key caution is its preview status: pin the model, measure real task performance, cap spend, and keep human or programmatic checks around consequential actions.
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