Gemini 3.1 Pro: Google’s Latest Multimodal Reasoning Model for Complex Tasks in 2026

On February 19, 2026, Google announced Gemini 3.1 Pro, the newest model in the Gemini 3 series and currently its most advanced model for complex tasks. Gemini 3.1 Pro builds on Gemini 3 Pro with a strong focus on deeper reasoning, long‑context understanding, and native multimodal input across text, images, audio, video, and code. ​⁠https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-1-pro/ ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

According to Google DeepMind’s model card, Gemini 3.1 Pro is a natively multimodal reasoning model designed to handle “vast datasets and challenging problems” across multiple input types, with a context window of up to 1 million tokens and up to 64K tokens of output. ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

What’s New in Gemini 3.1 Pro

Google describes Gemini 3.1 Pro as the upgraded “core intelligence” that powers recent advances such as Gemini 3 Deep Think. Compared to Gemini 3 Pro, 3.1 Pro brings:

• Stronger reasoning performance on difficult benchmarks such as ARC‑AGI‑2, academic reasoning tasks, and long‑horizon agent benchmarks.

• Improved multimodal capabilities, with native support for text, images, audio, video and code as inputs.

• Long‑context handling with up to 1M tokens in the context window, making it suitable for large documents, codebases, or multi‑file workflows.

• More capable agentic behavior, including tool use, function calling, search and code execution. ​⁠https://deepmind.google/models/gemini/pro/

Google highlights three main areas where Gemini 3.1 Pro is meant to shine:

• Learn anything: explain and reason about complex topics in clearer, more concise ways.

• Build anything: go from prompts or sketches to code, tools, and interactive experiences.

• Plan anything: support multi‑step planning and delegation for complex tasks. ​⁠https://deepmind.google/models/gemini/pro/

Key Capabilities

From the official DeepMind page and model card for Gemini 3.1 Pro, the headline capabilities include:

• Advanced reasoning with “unprecedented depth and nuance”

▫ Stronger performance on reasoning benchmarks, including ARC‑AGI‑2 (77.1% ARC Prize verified) and complex academic reasoning tasks such as Humanity’s Last Exam.

▫ Designed for problems that require more than a one‑shot answer, including multi‑step logic and algorithmic development. ​⁠https://deepmind.google/models/gemini/pro/

• Native multimodal understanding

▫ Inputs: text, images, audio, video, and entire code repositories.

▫ Outputs: text (up to 64K tokens).

▫ Intended for tasks that mix different media types: visual explanations, audio analysis, understanding video content, or reasoning across code and documentation. ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

• Long context

▫ Up to 1M input tokens in preview, with reported strong performance at 128K in long‑context benchmarks like MRCR v2.

▫ This allows Gemini 3.1 Pro to keep large numbers of documents, logs, or code files in memory at once. ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

• Agentic coding and tool use

▫ Improved performance on coding benchmarks such as SWE‑Bench, SWE‑Bench Pro, LiveCodeBench Pro, SciCode, and agentic coding tasks like Terminal‑Bench 2.0 and MCP Atlas.

▫ Supports function calling, structured output, search as a tool, and code execution, making it suitable for building code assistants and more autonomous agents. ​⁠https://deepmind.google/models/gemini/pro/

Benchmarks and Performance Highlights

The Gemini 3.1 Pro model card lists a series of benchmark results comparing 3.1 Pro (Thinking High) to Gemini 3 Pro and other leading models:

• ARC‑AGI‑2 (abstract reasoning puzzles):

▫ Gemini 3.1 Pro: 77.1% (ARC Prize verified)

▫ Gemini 3 Pro: 31.1%

▫ For context, other frontier models in the table score lower on this benchmark. ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

• Humanity’s Last Exam (academic reasoning, text + multimodal):

▫ Gemini 3.1 Pro: 44.4% (no tools) vs. Gemini 3 Pro: 37.5%. ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

• LiveCodeBench Pro (competitive programming, Elo):

▫ Gemini 3.1 Pro: 2887 vs. 2439 for Gemini 3 Pro and 2393 for a listed GPT‑5.x baseline. ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

• APEX‑Agents (long‑horizon professional tasks):

▫ Gemini 3.1 Pro: 33.5% vs. 18.4% for Gemini 3 Pro. ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

• BrowseComp (agentic search with tools):

▫ Gemini 3.1 Pro: 85.9% vs. 59.2% for Gemini 3 Pro, with competitive or better performance than other evaluated models. ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

Overall, the results in the model card show consistent gains over Gemini 3 Pro on tasks that involve reasoning, coding, tool use, multi‑step workflows, and long context, while staying competitive with or ahead of other frontier models in many categories.

Intended Use Cases

Google’s documentation and model card describe Gemini 3.1 Pro as particularly suited for:

• Agentic performance: building agents that can use tools, search, and code to complete multi‑step tasks.

• Advanced coding: competitive programming, large‑scale codebase assistance, algorithm design, and scientific coding.

• Long‑context and multimodal understanding: working across long documents, large data collections, or complex multimodal inputs like video plus transcripts.

• Algorithmic development and complex planning: situations where reasoning and step‑by‑step improvement matter more than single sentences of output. ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/ ​⁠https://deepmind.google/models/gemini/pro/

Concrete examples from Google’s blog and product page include:

• Code‑based animation: generating website‑ready, animated SVGs directly from text prompts.

• Complex system synthesis: configuring live telemetry streams to build dashboards (e.g., an aerospace dashboard for the ISS orbit).

• Interactive design: creating 3D simulations like a starling murmuration with hand‑tracking and generative audio.

• Creative coding: translating literary themes into functional code and modern web interfaces (e.g., a portfolio site inspired by “Wuthering Heights”). ​⁠https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-1-pro/ ​⁠https://deepmind.google/models/gemini/pro/

Where You Can Access Gemini 3.1 Pro

As of February 19, 2026, Gemini 3.1 Pro is in preview and is being rolled out across Google’s consumer, developer, and enterprise products. Specifically, Google lists the following access points:

• For developers (preview):

▫ Gemini API in Google AI Studio

▫ Gemini CLI

▫ The new agentic development platform Google Antigravity

▫ Android Studio integration ​⁠https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-1-pro/

• For enterprises:

▫ Vertex AI and Gemini Enterprise on Google Cloud ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

• For consumers:

▫ The Gemini app, with higher limits for Google AI Pro and Ultra plan users

▫ NotebookLM, where 3.1 Pro is available for Pro and Ultra users ​⁠https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-1-pro/

The DeepMind model card lists the distribution channels as:

• Gemini App

• Google Cloud / Vertex AI

• Google AI Studio

• Gemini API

• Google Antigravity

• NotebookLM ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

Status and Availability

• Gemini 3.1 Pro is currently labeled as Preview on the DeepMind site.

• Google states that they are releasing it in preview to validate updates, improve agentic workflows, and then move toward broader general availability.

• In the Gemini app and NotebookLM, availability is tied to Google AI Pro and Ultra subscription plans. ​⁠https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-1-pro/ ​⁠https://deepmind.google/models/gemini/pro/

For developers and enterprises, the recommended starting points are:

• Google AI Studio and the Gemini API for experimentation and prototyping.

• Vertex AI and Gemini Enterprise for production‑grade deployments.

• Google Antigravity for building more advanced agentic systems.

Safety and Limitations

The Gemini 3.1 Pro model card emphasizes:

• Safety performance broadly consistent with Gemini 3 Pro, with small improvements in automated safety metrics for text and multilingual content and small regressions in image‑to‑text safety, which Google says remain mostly non‑egregious based on manual review.

• The model remains below the critical capability levels (CCLs) for high‑risk domains such as CBRN, harmful manipulation, and machine‑learning‑R&D misuse, according to Google’s Frontier Safety Framework.

• Cyber capabilities have increased compared to Gemini 3 Pro, but remain below the threshold for critical concern, with mitigations in place. ​⁠https://deepmind.google/models/model-cards/gemini-3-1-pro/

As with earlier Gemini models, Google notes that Gemini 3.1 Pro:

• Can still make mistakes, hallucinate, or misinterpret prompts.

• Should be used with appropriate safeguards for high‑stakes domains.

• Is best used within the acceptable‑use policies and limitations detailed in the Gemini 3 Pro and 3.1 Pro model cards.

Summary

Gemini 3.1 Pro is Google’s new flagship Gemini 3‑series model for complex tasks in 2026. The key upgrades over Gemini 3 Pro include:

• Stronger performance on reasoning and coding benchmarks.

• A 1M‑token multimodal context window and 64K‑token outputs.

• Improved agentic capabilities, including tool use, code execution, and multi‑step tasks.

• Integration across the Gemini app, NotebookLM, Google AI Studio, Gemini API, Vertex AI, and Google Antigravity.

If you are already working in Google’s ecosystem and need a model for advanced coding, long‑context multimodal reasoning, and agentic workflows, Gemini 3.1 Pro is now the top‑end option available in preview.