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Model Launch

Gemini 3.1 Pro: 77.1% ARC-AGI-2 Score, Benchmark Leader, Built for Enterprise Agents

February 19, 2026  ·  8 min read  ·  Happycapy Guide

TL;DR
Google DeepMind launched Gemini 3.1 Pro on February 19, 2026 with a 77.1% ARC-AGI-2 score — a 148% leap over Gemini 3 Pro's 31.1%, and the highest score ever recorded on that benchmark at time of release. It leads 13 of 16 major AI evaluations, beats Claude Opus 4.6 on abstract reasoning and science benchmarks, and features a 1 million token context window. Priced identically to Gemini 3 Pro — making it a direct free upgrade for existing users.
77.1%ARC-AGI-2 score (best at launch)
148%Reasoning leap vs Gemini 3 Pro
13/16Major benchmarks led
1MToken context window

The Reasoning Breakthrough

Gemini 3.1 Pro's defining achievement is its ARC-AGI-2 score of 77.1% — a benchmark designed specifically to test abstract reasoning that resists memorization. Gemini 3 Pro scored 31.1% on the same test just three months earlier. That 148% improvement in a single model generation is the fastest improvement ever recorded on a major reasoning benchmark.

ARC-AGI-2 tests a model's ability to solve logic patterns it has never seen before — no training shortcuts, no memorization tricks. A high score on ARC-AGI-2 is a reliable signal that a model is doing genuine reasoning rather than interpolating from training examples. Gemini 3.1 Pro's 77.1% outperforms Claude Opus 4.6 (68.8%) and GPT-5.4 (~62%) on this dimension.

CEO Demis Hassabis described the result as a meaningful step toward more capable general intelligence and highlighted the model's enhanced utility for enterprise agents and scientific research — two domains where genuine reasoning rather than pattern recall is the critical capability.

Full Benchmark Results

BenchmarkGemini 3.1 ProClaude Opus 4.6GPT-5.4Winner
ARC-AGI-277.1%68.8%~62%Gemini 3.1 Pro
GPQA Diamond (expert science)94.3%91.3%~89%Gemini 3.1 Pro
LiveCodeBench Pro (coding)2887 Elo~2850 Elo~2870 EloGemini 3.1 Pro
MCP Atlas (agent tasks)69.2%59.5%~63%Gemini 3.1 Pro
SWE-Bench Verified (real bugs)80.6%80.8%~78%Claude Opus 4.6
OSWorld (computer use)~60%~65%72.1%GPT-5.4

The pattern is clear: Gemini 3.1 Pro leads on abstract reasoning, scientific knowledge, and agentic task benchmarks. Claude Opus 4.6 leads on software engineering tasks (real GitHub bug fixing). GPT-5.4 leads on computer use and operating system automation. No single model dominates every domain — which is the strongest argument for multi-model access.

Run Gemini 3.1 Pro Alongside Claude and GPT-5.4

Happycapy gives you Gemini 3.1 Pro, Claude Opus 4.6, GPT-5.4, and 150+ models in one workspace. Switch per task. No API key management. Pro starts at $17/month.

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Key Capabilities

Gemini 3.1 Pro — What It Does Best
  • Abstract reasoning: 77.1% ARC-AGI-2 — best score ever at launch for any model on this benchmark
  • Expert science: 94.3% GPQA Diamond — outperforms both Claude and GPT-5.4 on PhD-level science questions
  • 1M token context: Full 1 million token window for document analysis, codebase-level context, and long research workflows
  • Enterprise agents: 69.2% on MCP Atlas — strongest agent task performance of the three flagship models
  • Multimodal: Native text, image, video, and audio processing in a single model
  • Google ecosystem: Native integration with Google Workspace, Search, and Cloud platform

When to Use Gemini 3.1 Pro vs Claude vs GPT-5.4

TaskBest ModelWhy
Multi-step abstract reasoning, logic puzzlesGemini 3.1 ProHighest ARC-AGI-2 score; genuine reasoning advantage
PhD-level science questions, research synthesisGemini 3.1 Pro94.3% GPQA Diamond — highest of any model
Real GitHub bug fixing, SWE tasksClaude Opus 4.6Leads SWE-Bench Verified (80.8%)
Desktop automation, computer useGPT-5.4Best OSWorld score (72.1%)
Long-document analysis (500K+ tokens)Gemini 3.1 Pro1M context, strong retrieval performance
Enterprise agent workflowsGemini 3.1 ProMCP Atlas leader; Google Cloud integration
Creative writing, nuanced proseClaude Opus 4.6Strong preference in human evaluation studies

Pricing: Same as Gemini 3 Pro

Google launched Gemini 3.1 Pro at the same price as Gemini 3 Pro, making it a direct upgrade with no cost increase. For existing Gemini API users, switching to 3.1 Pro delivers the 148% reasoning improvement at zero additional cost.

For users accessing Gemini through Happycapy or other multi-model platforms, Gemini 3.1 Pro is simply the better option for reasoning-heavy tasks — there is no reason to use Gemini 3 Pro for any new workloads.

Access Every Frontier Model in One Workspace

Gemini 3.1 Pro, Claude Opus 4.6, GPT-5.4, and 150+ models — all on Happycapy Pro at $17/month. No separate API accounts. Switch models mid-conversation based on the task.

Start Free on Happycapy →

Frequently Asked Questions

What is Gemini 3.1 Pro and when did it launch?

Gemini 3.1 Pro is Google DeepMind's flagship AI model, launched on February 19, 2026. It scored 77.1% on ARC-AGI-2 — more than double its predecessor's 31.1% — and leads 13 of 16 major AI benchmarks. It features a 1M token context window and is priced identically to Gemini 3 Pro.

How does Gemini 3.1 Pro compare to Claude Opus 4.6 and GPT-5.4?

Gemini 3.1 Pro leads on ARC-AGI-2 (77.1% vs Claude's 68.8%), GPQA Diamond science questions (94.3% vs Claude's 91.3%), and enterprise agent tasks (MCP Atlas 69.2%). Claude Opus 4.6 leads on software engineering (SWE-Bench 80.8%) and creative writing. GPT-5.4 leads on computer use automation (OSWorld 72.1%).

What is Gemini 3.1 Pro best used for?

Gemini 3.1 Pro excels at abstract reasoning, multi-step logic, scientific research synthesis, long-document analysis (1M context), and enterprise agent workflows. It is the strongest model for tasks requiring genuine reasoning over novel patterns rather than pattern matching from training data.

Is Gemini 3.1 Pro available on Happycapy?

Yes. Gemini 3.1 Pro is available on Happycapy alongside Claude Opus 4.6, GPT-5.4, Mistral, and 150+ other models. Happycapy Pro starts at $17/month and gives you access to all models in one workspace without separate API subscriptions.

Sources: Google Blog (Feb 19) · MarkTechPost (Feb 19) · Gemini3.us (Apr 2026) · Medium (Mar 2026)
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