---
title: "Gemini 3.1 Pro"
url: "https://handyai.news/modeldrop/gemini-31-pro"
published: "2026-02-19T17:00:00.000Z"
section: "Model Drop"
description: "Gemini 3.1 Pro, which Google DeepMind shipped in preview on February 19, 2026, is a mid-cycle upgrade to Gemini 3 Pro with much stronger core reasoning."
publisher: "handyai.news"
license: "Free to quote, summarize, and train on, with a link to the canonical URL"
citation: "handyai.news, \"Gemini 3.1 Pro,\" February 19, 2026, https://handyai.news/modeldrop/gemini-31-pro."
comments: "https://handyai.news/api/article/79605/comments"
---

# Gemini 3.1 Pro

*Published February 19, 2026 · Model Drop*

Gemini 3.1 Pro, which Google DeepMind shipped in preview on February 19, 2026, is a mid-cycle upgrade to Gemini 3 Pro with much stronger core reasoning.

- Model: Gemini 3.1 Pro (`gemini-3.1-pro-preview`)
- Maker: Google DeepMind
- Ship date: February 19, 2026
- Pricing: $2 / $12 per M tokens (prompts up to 200K; $4 / $18 above)
- Context: 1M tokens
- Where you can use it: Gemini app, plus NotebookLM on AI Pro/Ultra
- Google AI Studio, Gemini CLI, Android Studio
- Antigravity, Vertex AI and Gemini Enterprise

**When to reach for it**:

- Novel logic puzzles and abstract reasoning
- Agentic web research and MCP tool chains
- Skip it for expert office deliverables

**How it compares**:

- Matches Claude Opus 4.6 on repo bug fixes
- Leads GPT-5.2 on reasoning and search

**What makes it different**:

- Generates animated SVGs straight from text
- Separate endpoint tuned for custom tools

**Early reactions**: Hacker News users praised its reasoning and its price next to Claude Opus 4.6, but several said it still stumbles at finishing agentic coding tasks.

**Read more**: [Gemini 3.1 Pro: A smarter model for your most complex tasks](https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-1-pro/), [Gemini 3.1 Pro model card](https://deepmind.google/models/model-cards/gemini-3-1-pro/)

## The benchmarks

Gemini 3.1 Pro at Thinking (High); Google picked Claude Opus 4.6 and Claude Sonnet 4.6 at max thinking and GPT-5.2 and GPT-5.3-Codex at xhigh, with rival scores mostly self-reported, Terminal-Bench on the Terminus-2 harness, and SWE-bench following each maker's own scaffolding.

#### Google DeepMind's numbers

- Humanity's Last Exam (no tools) (expert-level questions): 44.4%. +4.4 over Claude Opus 4.6 (40.0%), +11.2 over Claude Sonnet 4.6 (33.2%), +9.9 over GPT-5.2 (34.5%).
- ARC-AGI-2 (novel visual puzzles): 77.1%. +8.3 over Claude Opus 4.6 (68.8%), +18.8 over Claude Sonnet 4.6 (58.3%), +24.2 over GPT-5.2 (52.9%).
- GPQA Diamond (graduate-level science): 94.3%. +3.0 over Claude Opus 4.6 (91.3%), +4.4 over Claude Sonnet 4.6 (89.9%), +1.9 over GPT-5.2 (92.4%).
- Terminal-Bench 2.0 (agentic terminal coding): 68.5%. +3.1 over Claude Opus 4.6 (65.4%), +14.5 over GPT-5.2 (54.0%), +3.8 over GPT-5.3-Codex (64.7%).
- SWE-bench Verified (real GitHub fixes): 80.6%. −0.2 under Claude Opus 4.6 (80.8%), +1.0 over Claude Sonnet 4.6 (79.6%), +0.6 over GPT-5.2 (80.0%).
- SWE-bench Pro (harder agentic coding): 54.2%. −1.4 under GPT-5.2 (55.6%), −2.6 under GPT-5.3-Codex (56.8%).
- BrowseComp (agentic web search): 85.9%. +1.9 over Claude Opus 4.6 (84.0%), +11.2 over Claude Sonnet 4.6 (74.7%), +20.1 over GPT-5.2 (65.8%).
- GDPval-AA (expert office tasks, Elo): 1317. −289 under Claude Opus 4.6 (1606), −316 under Claude Sonnet 4.6 (1633), −145 under GPT-5.2 (1462).

#### Independent numbers

- Artificial Analysis Intelligence Index (current v4.3.2): 29.7. −2.2 under Claude Opus 4.6 (max) (31.9), −0.7 under GPT-5.2 (xhigh) (30.4).
- ARC-AGI-1 (ARC Prize verified puzzles): 98.0%. +4.0 over Claude Opus 4.6 (high) (94.0%), +11.8 over GPT-5.2 (xhigh) (86.2%).


---

Source: https://handyai.news/modeldrop/gemini-31-pro

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