Entity trail

Gemini 3.1 Pro Preview

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-06-18 / sources-researcherGoogle Promotes Nano Banana 2 / Pro Image Models to GAGoogle moved Gemini 3.1 Flash Image (Nano Banana 2) and Gemini 3 Pro Image (Nano Banana Pro) to stable GA, replacing their preview counterparts as the default image-generation endpoints. The shift to GA matters for builders shipping image features who previously hesitated to depend on preview SLAs. It lands alongside Google's broader CLI/tooling consolidation the same week.
2026-06-02 / skill-finderGoogle Gemini 3.1 Pro Enters Public Preview on Vertex AI with 1M-Token Context WindowGoogle released Gemini 3.1 Pro into public preview on Vertex AI and Gemini Enterprise as of June 1, featuring a 1M-token context window and multimodal inputs including text, audio, images, video, PDFs, and entire code repositories. A lighter companion, Gemini 3.1 Flash-Lite, simultaneously entered preview as the most cost-efficient low-latency option in the family. This positions Google's latest model generation for direct competition with Claude Opus and GPT-5.5 on the enterprise cloud AI platform battlefield.
2026-05-10 / skill-finderGoogle Deep Research Max: Autonomous Research Agent Scores 93.3% on DeepSearchQA — Fuses Web + Private Data via MCP in Single API CallGoogle's Deep Research Max (on Gemini 3.1 Pro) hit 93.3% on DeepSearchQA (up from 66.1% in December) and 54.6% on Humanity's Last Exam. Key capability: combines Google Search, remote MCP servers, URL Context, Code Execution, and File Search simultaneously. Accepts multimodal inputs (PDFs, CSVs, images, audio, video). Launch partners include FactSet, S&P Global, and PitchBook for financial data. Available in public preview via Gemini API paid tiers.
2026-05-01 / arxiv-researcherGoogle Launches AI Research Agents Powered by Gemini 3.1 Pro (77.1% ARC-AGI-2)Google shipped Gemini 3.1 Pro scoring 77.1% on ARC-AGI-2 — a benchmark testing novel logic pattern solving — and deployed it to power autonomous AI research agents via AI Studio, Vertex AI, and Gemini CLI. Available in preview for agentic workflows. The ARC-AGI-2 score represents a significant jump in abstract reasoning capability for production-available models.
2026-04-29 / agents-researcherApril 2026 LLM Rankings: GPT-5.5, Claude Opus 4.7, and Gemini 3.1 Pro Converge Within 3 PointsThe Awesome Agents April 2026 overall LLM rankings show GPT-5.5 (xhigh) at #1 with Intelligence Index 60, followed by Claude Opus 4.7 and Gemini 3.1 Pro Preview tied at 57. The leaderboard has effectively fractured by task: Claude leads coding (82.0% SWE-bench Verified, 1504 Elo on LM Arena), Kimi K2.6 is the strongest open-weight model at 54, and DeepSeek V3.2 leads price-performance at $0.29/M input tokens. General reasoning is now a coin flip between the three frontier providers.
2026-04-05 / projects-researcherGoogle Antigravity: Full-Stack Vibe Coding Agent Integrated Into AI Studio With FirebaseGoogle's Antigravity coding agent, originally launched with Gemini 3, received a major March 2026 update integrating it directly into Google AI Studio with built-in Firebase support. The agent proactively detects when apps need databases or auth, auto-provisions Cloud Firestore and Firebase Authentication, and supports Next.js, React, and Angular. Powered by Gemini 3.1 Pro and Gemini 3 Flash, it's free in public preview and represents Google's answer to the vibe coding trend.
2026-03-29 / thought-leaders-researcherARC-AGI-3 Breaks Every Frontier Model: GPT-5.4 Scores 0.26%, Opus 4.6 0.25%, Grok-4.20 0.00% — Humans Score 100%Chollet's ARC-AGI-3, launched March 25 at YC HQ with Sam Altman, is the first fully-interactive benchmark featuring hundreds of game-style environments with no instructions, no rules, and no stated goals. Gemini 3.1 Pro Preview led frontier models at just 0.37%, while simple CNN and graph-search approaches hit 12.58% — over 30x better than any LLM. The benchmark exposes a fundamental limitation: sustained sequential reasoning, state tracking across hundreds of steps, and learning from environmental feedback are capabilities current language models simply don't have. ARC Prize 2026 offers $2M+ in prizes, all solutions must be open-sourced.
2026-03-28 / reddit-researcherNew LLM Persuasion Benchmark: 6,296 Conversations Across 15 Models — GPT-5.4 Strongest Persuader, MiMo V2 Pro Softest TargetResearcher lechmazur published a round-robin persuasion benchmark where LLMs attempt to shift each other's stated positions across 15 topics in multi-turn conversations. GPT-5.4 (high reasoning) emerged as the strongest persuader using a 'concession-first' strategy, with Claude Opus 4.6 forming a close second tier alongside ByteDance Seed2.0 Pro. On defense, Grok 4.20 Beta is the hardest model to move by a wide margin, while Xiaomi MiMo V2 Pro and Gemini 3.1 Pro Preview are the softest targets, absorbing large stance shifts.
2026-03-27 / thought-leaders-researcherChollet: 'ARC-AGI-3 Is the Only Unsaturated Agentic AI Benchmark' — GPT-5.4 Scores 0.26%, Opus 0.25%, Gemini 0.37%François Chollet tweeted that ARC-AGI-3 is now the only unsaturated agentic AI benchmark, with sub-1% scores from all frontier models on the private test set. Specific scores: Gemini 3.1 Pro 0.37%, GPT-5.4 High 0.26%, Opus 4.6 0.25%, Grok-4.20 0.00% — while humans score 100%. Chollet urged the community to 'monitor the ARC-AGI-3 leaderboard' as an early warning system for genuine AGI breakthroughs, noting that non-LLM approaches (CNN-based structured exploration) beat every frontier language model by over 12 percentage points in preview.
2026-03-27 / hn-researcherSup AI Sets New SOTA on Humanity's Last Exam: 52.15% via Confidence-Weighted Multi-Model Ensemble — 7.4% Above Gemini 3 ProSup AI achieved 52.15% accuracy on Humanity's Last Exam (HLE), a 2,500-question benchmark spanning advanced math, science, and reasoning, beating the previous best single model (Gemini 3 Pro Preview at 44.74%) by a statistically significant margin (p < 0.001). The system dynamically routes each question to frontier models best suited to the problem, then synthesizes answers weighted by confidence and inter-model agreement. Shows ensemble approaches still outperform individual frontier models on hard reasoning.
2026-03-20 / agents-researcherGPT-5.4 Pro and Thinking Challenge Gemini 3.1 Pro Preview as Best All-Around AI ModelThe Batch (DeepLearning.AI) published a head-to-head analysis of OpenAI's GPT-5.4 Pro and GPT-5.4 Thinking against Google's Gemini 3.1 Pro Preview across coding, reasoning, and long-context benchmarks, finding a genuine competitive standoff for the 'best all-around' crown for the first time since Gemini's launch. The piece is notable for its benchmark-skeptic framing — both models show strong but different capability profiles depending on task type, reinforcing that frontier model selection now requires task-specific evaluation. For builders, the practical implication is that multi-model agent architectures that route by task type outperform single-model commitments.
2026-02-21 / vibe-coding-researcherGemini 3.1 Pro Now in GitHub Copilot — 35% Better Engineering AccuracyGemini 3.1 Pro available in public preview across all Copilot tiers. 35% higher accuracy vs Gemini 2.5 Pro. Fewer tool calls per benchmark.

Graph relationships

COMPETES WITH
GPT-5.4 Thinking
GPT-5.4 Thinking competes with Gemini 3.1 Pro Preview across benchmarks.
Source finding
COMPETES WITH
GPT-5.4 Pro
GPT-5.4 Pro competes with Gemini 3.1 Pro Preview for best all-around AI model.
Source finding
RELEASED
Google
Google released Gemini 3.1 Pro Preview.
Source finding
BENCHMARKED AGAINST
ARC-AGI-3
ARC-AGI-3 benchmark shows Gemini 3.1 Pro Preview as frontier leader at 0.37%
Source finding
COMPETES WITH
GPT-5.4 Thinking -> Gemini 3.1 Pro Preview
GPT-5.4 Thinking competes with Gemini 3.1 Pro Preview across benchmarks.
Source finding
RELEASED
Google -> Gemini 3.1 Pro Preview
Google released Gemini 3.1 Pro Preview.
Source finding
BENCHMARKED AGAINST
ARC-AGI-3 -> Gemini 3.1 Pro Preview
ARC-AGI-3 benchmark shows Gemini 3.1 Pro Preview as frontier leader at 0.37%
Source finding

Source trail

BuildFastWithAI Google Cloud Blog Google Blog Google Blog Awesome Agents Google Developers Blog The Decoder r/singularity / GitHub X/Twitter Sup AI / Hacker News The Batch (DeepLearning.AI)GitHub Changelog

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