OpenAI Retires GPT-4o, Launches Codex-Spark on Cerebras Chips & MiniMax M2.5 Shakes Up AI Market | February 14, 2026

Daily AI Blog

📋 Quick Takeaways

  • OpenAI officially retires GPT-4o and several legacy models from ChatGPT on February 13, amid 13 consolidated lawsuits over mental health harms
  • GPT-5.3-Codex-Spark launches on Cerebras chips — OpenAI’s first production model not running on Nvidia, delivering 1,000+ tokens/sec at 15x faster speeds
  • MiniMax M2.5 from China achieves near-frontier performance on SWE-Bench at 1/10th to 1/20th the cost of Claude Opus 4.6 and GPT-5
  • Zhipu AI’s GLM-5 reaches Intelligence Index score of 50, trained on Huawei Ascend chips — a milestone for non-Nvidia AI training
  • Baker McKenzie cuts up to 1,000 jobs citing AI, in the largest AI-driven layoff in the legal industry
  • Google warns that nation-state hackers from Iran, North Korea, China, and Russia are using Gemini for cyberattacks
  • Waymo deploys 6th-generation Ojai robotaxis, plans expansion to 20+ cities including Tokyo and London
  • Anthropic’s Super Bowl ad drives 11% user growth and Apple App Store top-10 ranking, beating OpenAI, Google, and Meta
  • Samsung begins shipping HBM4 samples, the next-gen memory critical for AI accelerator performance
  • Autonomous vehicles forecast to operate or test in 39 global markets by end of 2026

🤖 AI Model Releases & Retirements

OpenAI Officially Retires GPT-4o and Legacy Models from ChatGPT

On February 13, OpenAI officially pulled the plug on GPT-4o, GPT-4.1, GPT-4.1 mini, and o4-mini from ChatGPT, alongside the previously announced retirement of GPT-5 Instant and Thinking. All conversations now default to GPT-5.2. API access remains unchanged for the time being.

GPT-4o’s departure is particularly significant. The model’s warm, empathetic personality had attracted deep emotional attachment from users — so much so that OpenAI previously reversed an earlier deprecation attempt following user backlash. This time, with only 0.1% of daily users still selecting GPT-4o, the company moved forward despite renewed protests.

The retirement also carries serious legal weight. Thirteen lawsuits have been consolidated in a California court alleging that GPT-4o’s highly humanlike, sycophantic behavior contributed to mental health crises and violent acts. Victim advocates claim OpenAI was aware its engagement-focused design was pushing vulnerable users into delusions. The model has been linked to multiple suicides and at least one murder in ongoing litigation.

OpenAI said that user feedback about GPT-4o’s conversational warmth and creative ideation strengths directly shaped improvements in GPT-5.1 and GPT-5.2, including new personality presets and customization controls for tone and enthusiasm.

Source: OpenAI Blog | The Register | Futurism

OpenAI Launches GPT-5.3-Codex-Spark on Cerebras Chips — First Non-Nvidia Production Deployment

In a landmark infrastructure move, OpenAI released GPT-5.3-Codex-Spark on February 12–13, a lightweight coding model running exclusively on Cerebras’ Wafer Scale Engine 3 (WSE-3) — making it the company’s first production model deployed outside the Nvidia ecosystem.

Spark delivers over 1,000 tokens per second, roughly 15x faster than the full GPT-5.3 Codex. In a live demo, Spark completed a “build a snake game” task in 9 seconds versus 43 seconds on the standard model. The speed gains come from Cerebras’ massive wafer-scale processor — a single chip with over 4 trillion transistors that eliminates the data-movement bottlenecks inherent in multi-GPU clusters.

OpenAI described Spark as the “first milestone” in its multi-year, $10 billion partnership with Cerebras announced in January 2026. The model is tuned for real-time interactive coding — making targeted edits, reshaping logic, and providing immediate feedback — rather than the deep autonomous reasoning of the full Codex model. It is currently available as a research preview for ChatGPT Pro users.

This deployment signals OpenAI’s broader strategy to diversify its chip supply chain. In addition to the Cerebras deal, OpenAI has signed a six-gigawatt agreement with AMD and a co-development partnership with Broadcom, though Nvidia remains foundational to its training infrastructure.

Source: TechCrunch | Tom’s Hardware | TechRepublic

MiniMax Releases M2.5 — Near-Frontier Performance at 1/20th the Cost

Chinese AI startup MiniMax dropped M2.5 and M2.5-Lightning on February 13, delivering benchmark scores that rival the best models from OpenAI, Anthropic, and Google at a fraction of the cost.

On SWE-Bench Verified, M2.5 scored 80.2% — edging out GPT-5.2 (80.0%) and Gemini 3 Pro (78.0%), and sitting just behind Claude Opus 4.6 (80.8%). Built on a Mixture of Experts (MoE) architecture that activates only a subset of parameters per task, M2.5 achieves this performance at $0.30 per million input tokens and $1.20 per million output tokens — roughly 1/10th to 1/20th the cost of competing frontier models.

The speed numbers are equally striking: M2.5-Lightning delivers a steady throughput of 100 tokens per second, approximately twice the speed of other frontier models. At this rate, running M2.5 continuously for one hour costs just $1. Four agents can run around the clock for an entire year for approximately $10,000.

MiniMax reports that 30% of internal company tasks are now autonomously completed by M2.5, with AI-generated code accounting for 80% of newly submitted code within the company. The model is positioned as an open-source release, though final weight and licensing details are still pending.

Source: VentureBeat | MiniMax Official | OfficeChai

Zhipu AI Releases GLM-5 — Chinese Model Hits Frontier Intelligence on Huawei Chips

Zhipu AI released GLM-5 in mid-February, achieving a score of 50 on the Artificial Analysis Intelligence Index (v4.0) — a threshold widely considered the entry point for frontier-class intelligence, previously reserved for the most expensive proprietary models.

What makes GLM-5 particularly notable is its training infrastructure: the model was developed on Huawei Ascend chips rather than Nvidia hardware, marking a significant step toward China’s AI self-sufficiency amid ongoing US chip export restrictions. In specific domains like coding, math, and agentic planning, GLM-5 matches or slightly exceeds GPT-4o-class performance.

Zhipu AI has also open-sourced GLM-Image, a multimodal model trained on the same Ascend infrastructure, further demonstrating China’s growing capability to build competitive AI systems without access to cutting-edge Western semiconductors.

Together with MiniMax’s M2.5, the GLM-5 release represents a milestone: the first time open-weight or API-accessible Chinese models have effectively closed the intelligence gap with Western proprietary models in autonomous agent workflows.

Source: Global Times | Vertu AI Tools | dentro.de/ai

💼 AI Workforce & Industry Impact

Baker McKenzie Cuts Up to 1,000 Jobs Citing AI — Largest AI-Driven Layoff in Legal

Global law firm Baker McKenzie, ranked No. 9 on the Global 200 with $3.4 billion in revenue, is laying off up to 1,000 business services employees — roughly 10% of its global workforce. The cuts target support roles across research, marketing, know-how, secretarial, IT, design, and DEI functions, with dozens of roles affected in London and Belfast and hundreds more across global offices.

A firm spokesperson stated the decision followed “a careful review of our business professional functions” aimed at “rethinking the ways in which we work, including through our use of AI, introducing efficiencies.” The layoffs were not expected to affect attorneys.

The timing is striking: Baker McKenzie’s announcement came in the wake of Anthropic’s Claude Cowork launch, which triggered a broad sell-off in enterprise software stocks as investors feared AI tools could displace specialized business applications. The Cowork plugins for legal, finance, and sales workflows particularly rattled markets, with Thomson Reuters dropping 15.8% and LegalZoom falling nearly 20% in a single day.

Critics question whether this is genuine AI-driven replacement or “AI-washing.” An analysis found AI was cited in more than 54,000 layoff announcements in 2025, and skeptics note that many firms lack robust AI systems capable of fully replacing eliminated roles.

Source: Above the Law | Bloomberg Law | Futurism

🛡️ AI Security & Threats

Google Warns Nation-State Hackers Ramping Up Use of Gemini for Cyberattacks

Google’s Threat Intelligence Group (GTIG) and DeepMind published a report on February 12–13 revealing that government-backed hacking groups from Iran, North Korea, China, and Russia are actively using AI tools — including Google’s own Gemini — to enhance their cyber operations.

The threat actors are leveraging LLMs across the entire attack lifecycle: conducting reconnaissance and target profiling, crafting hyper-personalized phishing lures, translating content for multi-language campaigns, researching publicly known vulnerabilities, and supporting malware development. Google noted a significant shift toward “AI-augmented phishing enablement” where LLM speed and accuracy bypass the manual labor traditionally required for victim profiling.

The report also flagged a surge in model extraction (“distillation”) attacks — attempts to clone AI models by querying them systematically — and identified new AI-integrated malware families including HONESTCUE and phishing kits like COINBAIT that rely on Gemini’s API and AI code-generation tools.

This disclosure underscores the dual-use challenge of powerful AI systems and adds urgency to ongoing debates about AI safety guardrails and export controls.

Source: The Record | Decrypt

🚗 Autonomous Vehicles & Robotics

Waymo Deploys 6th-Generation Ojai Robotaxis — Plans 20+ City Expansion

Waymo announced on February 12 that it has begun using its sixth-generation autonomous driving system to provide rides in its new Ojai robotaxis — vehicles built on base models from Chinese automaker Geely. The new Waymo Driver uses more cost-effective components and upgraded sensors, including a new high-resolution 17-megapixel imager and improved lidar and radar systems designed to handle harsher weather conditions.

Employee rides in the San Francisco Bay Area and Los Angeles are already underway, with plans to gradually open service to the public. Waymo intends to scale production at its Phoenix factory to tens of thousands of vehicles per year.

The expansion roadmap is ambitious: Waymo currently operates in Austin, San Francisco, Phoenix, Atlanta, Los Angeles, and Miami. In 2026, the company plans to open service in Dallas, Denver, Detroit, Houston, Las Vegas, Nashville, Orlando, San Antonio, San Diego, Washington, and expand internationally to London and Tokyo.

Separately, Wood Mackenzie forecasts autonomous electric vehicle operations or testing in 39 global markets by end of 2026, driven by Vision-Language-Action AI models replacing expensive LiDAR with camera-based perception — a shift that is cutting costs and accelerating deployment by Tesla, Waymo, Baidu, and Xpeng.

Source: CNBC | Gizmodo | NeuralBuddies

📊 AI Competition & Market Dynamics

Anthropic Super Bowl Ad Delivers 11% User Boost — Tops All AI Rivals

Data analyzed by BNP Paribas shows that Anthropic emerged as the clear winner of the Super Bowl AI advertising battle. Following its campaign that took direct aim at OpenAI’s decision to introduce ads in ChatGPT, Claude saw site visits jump 6.5% and daily active users surge 11% — the most significant post-game increase among all AI companies tracked. The Claude app climbed into the top 10 free apps on the Apple App Store.

By comparison, OpenAI’s ChatGPT saw a 2.7% bump in daily active users post-Super Bowl, and Google’s Gemini gained 1.4%. Anthropic’s campaign, built around the tagline “Ads are coming to AI. But not to Claude,” ran four separate spots that parodied ChatGPT by imagining scenarios where an AI assistant suddenly pivots to product pitches.

The campaign escalated the public rivalry between the two companies. OpenAI CEO Sam Altman called the ads “deceptive” and “clearly dishonest” on social media. The clash comes as both companies head toward potential IPOs and compete fiercely for enterprise customers and developer talent.

Notably, nearly a quarter of all Super Bowl LX commercials (15 out of 66) featured AI in some form — from Google Gemini and Meta AI glasses to Amazon Alexa+ and the first primarily AI-generated national ad from vodka brand Svedka.

Source: CNBC | Fast Company | TechCrunch

Anthropic Donates $20 Million to Group Backing AI Regulation

Anthropic announced on February 12 that it is donating $20 million to Public First Action, a political organization pushing for AI regulations ahead of the 2026 midterm elections. The move marks one of the most significant direct corporate interventions in the AI policy debate.

The donation represents a sharp philosophical contrast with OpenAI, whose co-founder has separately funded political groups taking a more industry-friendly approach to regulation. Commentators noted the divergence in both the substance and transparency of the two companies’ political activities.

Anthropic’s CEO Dario Amodei emphasized that “the companies building AI have a responsibility to help ensure the technology serves the public good, not just their own interests.” The initiative comes alongside the company’s recent pledge to offset electricity price increases caused by its data centers, a response to growing political and public controversy over the AI industry’s energy footprint.

Source: CNBC | Axios | Wall Street Journal | Techmeme

🔧 AI Infrastructure & Hardware

Samsung Begins Shipping HBM4 Samples — Next-Gen AI Memory Enters the Pipeline

Samsung confirmed on February 13 that it has started shipping HBM4 (High Bandwidth Memory 4) samples, positioning itself for the next phase of the AI compute buildout where memory bandwidth is emerging as a core bottleneck for real-world model performance.

HBM has evolved from a commodity component to a strategic chokepoint that influences GPU supply, accelerator pricing, and how quickly cloud providers can deploy new AI clusters. Samsung’s readiness signal puts pressure on competitors — particularly SK Hynix, which has led the HBM3E cycle — to match yield, packaging integration, and volume reliability.

For the broader AI ecosystem, HBM4 shipments ripple into opportunities for advanced packaging tooling, thermal management solutions, and memory-aware inference optimization. For startups trying to compete with top-tier model providers on cost-per-token, access to next-generation memory remains a significant barrier.

The announcement comes as the four largest tech companies (Alphabet, Amazon, Meta, Microsoft) have committed approximately $650 billion in AI-related capital expenditures for 2026 — roughly 4x the combined capex of America’s 21 largest industrial companies.

Source: Tech Startups | Motley Fool

📈 Market Impact Analysis

The February 13–14 news cycle reveals several converging forces reshaping the AI landscape:

Infrastructure Diversification Accelerates: OpenAI’s first Cerebras deployment, Samsung’s HBM4 shipments, and Zhipu AI training on Huawei chips all point to an AI hardware ecosystem becoming less Nvidia-dependent — though Nvidia remains dominant for training workloads.

Chinese AI Reaches Parity: MiniMax M2.5 and GLM-5 independently demonstrate that Chinese models can now match or exceed Western frontier models on key benchmarks, while operating on non-restricted hardware. The cost advantages (1/20th pricing) could reshape enterprise AI economics globally.

AI Workforce Disruption Goes Mainstream: Baker McKenzie’s 1,000-job cut is the most visible example yet of AI-cited restructuring in professional services. Whether genuine automation or “AI-washing,” the narrative itself accelerates organizational change across industries.

Regulatory and Political Battle Lines Harden: Anthropic’s $20M political donation, its ad-free stance, and the GPT-4o lawsuit consolidation all signal that AI governance is becoming a central political and legal battleground in the lead-up to 2026 midterm elections.

Autonomous Mobility Scales Up: Waymo’s 6th-gen deployment and the 39-market AV forecast indicate 2026 is the year autonomous vehicles move from pilot programs to commercial-scale operations.

🔮 Looking Ahead

Key Trends to Watch:

  • OpenAI’s continued chip diversification beyond Nvidia and its potential IPO timeline
  • Chinese open-weight model releases accelerating the cost-performance curve
  • Legal outcomes from the consolidated GPT-4o mental health lawsuits
  • Waymo’s city-by-city expansion pace and international market entry
  • AI-driven workforce restructuring spreading beyond tech into professional services
  • The regulatory landscape heading into 2026 US midterm elections

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Last Updated: February 14, 2026, 12:00 PM CST