**Google’s Titans & Gemini 3 Dominate AI Benchmarks as OpenAI Rushes GPT-5.2 for December Showdown**

Major AI Model Releases & Benchmarks

Google’s "Titans" AI Achieves 70% Recall & Reasoning on BABILong Benchmark
Google’s Titans model, leveraging the MIRAS architecture, has reached 70% recall and reasoning accuracy on the BABILong benchmark, a significant leap in long-term memory capabilities for AI. This breakthrough could enable more advanced applications in natural language processing and extended-context tasks.

• Google's 'Titans' achieves 70% recall and reasoning accuracy on ten million tokens in the BABILong benchmark
  • Google Research Blog: Titans & MIRAS

Google’s Gemini 3 Pro Vision Outperforms Claude Opus 4.5 & GPT-5.1 in Multimodal Benchmarks
Gemini 3 Pro Vision has surpassed competitors in visual reasoning, video understanding, and spatial reasoning, marking a major advancement in multimodal AI capabilities.

• Gemini 3 Pro Vision benchmarks: Finally compares against Claude Opus 4.5 and GPT-5.1
  • Google Blog: Gemini 3 Pro Vision

DeepSeek V3.2 (14.9%) Outperforms GPT-5.1 (9.5%) on Cortex-AGI at 124.5x Lower Cost
DeepSeek’s latest model has achieved higher scores on the Cortex-AGI benchmark while being drastically more cost-effective, highlighting the accelerating pace of AI efficiency improvements.

• DeepSeek V3.2 (14.9%) scores above GPT-5.1 (9.5%) on Cortex-AGI despite being 124.5x cheaper

OpenAI vs. Google: Competitive Escalation

OpenAI Accelerates GPT-5.2 Release to December 9th in "Code Red" Response to Gemini 3
OpenAI has fast-tracked the launch of GPT-5.2 to counter Google’s Gemini 3, prioritizing improvements in speed, reasoning, and coding. The company has paused other projects to focus on this update.

• BREAKING: OpenAI declares Code Red & rushing "GPT-5.2" for Dec 9th release to counter Google
  • The Verge: OpenAI’s "Code Red"
• Report: OpenAI planning new model release for Dec 9th to counter Gemini 3
  • The Verge: GPT-5.2 Release Details

Open-Source & Developer Tools

Essential AI Releases Rnj-1: A High-Performance 8B-Parameter Open-Source LLM for Code & STEM
Rnj-1, an open-source 8B-parameter model optimized for coding and STEM tasks, has been released on Hugging Face, offering strong benchmark performance.

• The Best Open-Source 8B-Parameter LLM Built in the USA
  • Hugging Face: Rnj-1 Collection

FlowCoder: Visual Workflow Customization for AI Coding Agents (Claude Code, Codex)
FlowCoder introduces a visual flowchart builder to streamline multi-step workflows for AI coding agents, reducing errors like skipped steps and repetitive prompts.

• FlowCoder: Visual agentic workflow customization for Claude Code and Codex
  • GitHub: FlowCoder
  • Demo Video

AI Governance & Testing Methodologies

Maxim Introduces Agent API Endpoint Evaluation for Real-World AI Validation
A new testing method validates AI agent outputs by sending them to production APIs, ensuring correctness against real-system requirements—particularly useful for content generation and structured outputs.

• (Note: Original post title misattributed to Geoffrey Hinton; corrected based on summary content.)
• Geoffrey Hinton says rapid AI advancement could lead to social meltdown if it continues without guardrails
  • The Mirror: AI Testing Methodology (Link may not match summary; verify source.)

Geoffrey Hinton Warns of "Social Meltdown" Without AI Guardrails
AI pioneer Geoffrey Hinton cautioned that unchecked AI advancement could lead to societal instability, emphasizing the need for regulatory safeguards.

• (Same post as above; summary discrepancy noted.)