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Il y a des stratégies qui vieillissent bien. Celle qu'a déployée Google avec Android à la fin des années 2000 en fait partie, et Google DeepMind semble décidé à la recycler pour la robotique. C'est en tout cas ce qui ressort de la première grande interview de Koray Kavukcuoglu depuis sa prise de fonction à la tête de Google DeepMind, accordée la semaine dernière à …

Google on Wednesday said it would withhold its most powerful artificial intelligence model from the public for now, releasing Gemini 4 Argon only to a vetted group of cybersecurity experts to avoid misuse by hackers. “Safely releasing frontier capabilities at this level requires a phased approach,” wrote Koray Kavukcuoglu, Google’s chief AI architect, in a blogpost announcing the model. Google said it was voluntarily giving the US government early access to the model and would gather feedback from testers before making it widely available. The cautious rollout mirrors the approach of rival Anthropic, which has kept its most advanced model, Claude Mythos Preview, restricted to a small number of trusted organizations. Washington briefly forced Anthropic to suspend access to its publicly released Claude Mythos and Claude Fable models in June, and has since set up a voluntary process for vetting the most powerful AI models before release. The announcement came a day after Donald Trump hosted top tech executives, including the Google chief, Sundar Pichai, and Anthropic’s Dario Amodei, at the White House, where they signed a voluntary accord pledging to police the risks of their own AI systems. Cybersecurity experts fear the state-of-the-art technology could be used to hack...

Google on Wednesday announced its latest frontier artificial intelligence (AI) model, Gemini 4 Argon, that it said is being rolled out to a set of trusted cyber defenders through its Fairwind Program. "It delivers frontier performance in complex workflows across real-world software engineering, enterprise knowledge work like legal and finance, and cybersecurity defense," Koray Kavukcuoglu,

Google on Wednesday said it would withhold its most powerful artificial intelligence model from the public for now, releasing Gemini 4 Argon only to a vetted group of cybersecurity experts to avoid misuse by hackers. “Safely releasing frontier capabilities at this level requires a phased approach,” wrote Koray Kavukcuoglu, Google’s chief AI architect, in a blog post announcing the model.

Cumhurbaşkanı Recep Tayyip Erdoğan, Türkiye Büyük Millet Meclisi (TBMM) Genel Kurulu'nda yeni yasama yılı açılışını gerçekleştirdi. Bu toplantı, 51 gün araya geçen yasama çalışmalarına devam edilmesi… · Photo : Koray · CC BY-SA · Wikimedia

> **Attributed compile (not original research)** > > **Primary source:** Gemini 4 Argon: our next era of frontier intelligence by **Koray Kavukcuoglu** (Google DeepMind / Google blog), published **2026-09-30** > > **Secondary roundup:** Google announces Gemini 4 Argon as its new frontier model (9to5Google), published **2026-09-30** > > **Optional context:** Google's first Gemini 4 model is 'Argon' (Engadget), published **2026-10-01** > > **Contrast only (not the headline):** Introducing GPT-6.1 Sol (OpenAI) and GPT-6.1 Sol in GitHub Copilot (GitHub Changelog), both **2026-09-29** > > This post restates Googles launch packaging in my own words, with a builder checklist for what to do _before_ a public model ID exists. **I did not run Gemini 4 Argon** it is not publicly available yet. Every price, benchmark, and access claim below is vendor-reported (or clearly attributed to a named secondary source). Google announced **Gemini 4 Argon** on September 30, 2026, as its next frontier model after the Gemini 3.x line. The capability story is long-horizon software engineering, enterprise knowledge work, and defensive cybersecurity. The access story matters more for builders this week: Argon is live only inside Google’s **Fairwind Program** for trusted cyber defenders. Broader rollout is “soon,” starting with paid API customers and Google AI Ultra subscribers. There is **no public model ID** and **no first-call snippet** for general developers yet. That phased release is the difference between bookmark the blog” and “ship a production default tomorrow.” ## What Google announced (and why Fairwind-first matters) Per Kavukcuoglu’s post, Argon is built for deep reasoning across complex, multi-step workflows. Google says it is already using Argon internally (thousands of Googlers, vendor claim) for specialized coding, research, and writing. External access starts with Fairwind — and for trusted defenders plus Google’s own teams, Google will ship a version **without cyber guardrails** so they can use full defensive capability. For everyone else, Google is still iterating on safeguards (misuse including CBRN/cyber, prompt injection, misalignment monitoring of chain-of-thought and actions, and hardened sandboxes) while engaging the U.S. government’s voluntary pre-release process. Treat Fairwind-only as a hard product constraint: **do not plan a customer-facing pipeline on Argon until you have a documented API model ID and a paid access path.** ## Pricing trap: intro $2/$10 vs post-intro $4/$20 Googles stated launch pricing (vendor): Per 1M tokens (Google) | Introductory | After intro period ---|---|--- Input | **$2** | **$4** Output | **$10** | **$20** Cached input | **95% off** input price | same discount structure stated at launch Intro sticker matches the familiar **$2 / $10** band many teams already budget for mid-frontier coding models. After the introductory period, Google says rates move to **$4 / $20** — Opus-class list territory. Cached input at **95% off** input price is the quiet lever: long agent loops that re-send the same system prompt, repo summary, or tool schema will live or die on cache hit rate once Argon is in the API. Build cost models for **both** columns now. An eval that looks cheap at intro rates can double on input/output when the promo ends. Do not bake “Argon is $2/$10 forever” into a board deck. ## Why 1M _output_ tokens changes agent design Google expands Argon’s **output** token limit to **1M** , up from **64K** — framed as industry-leading generation headroom for long trajectories. Context-window talk is saturated. Output headroom is different: one trajectory can think, tool-call, revise, and emit a large artifact (migration plan, multi-file patch set, research memo) without mid-flight truncation. Loops designed for 64K128K completions assume early summarization or multi-turn “continue. A 1M ceiling (once callable) means fewer artificial breakpoints — and more runaway-spend risk. Add budgets, stop conditions, and per-step logs _before_ you get an API key. ## Vendor benchmarks (labeled as such) These figures come from Google’s announcement and secondary reporting. They are **not** my harness results. Benchmark (vendor-reported) | Gemini 4 Argon | Notes ---|---|--- DeepSWE v1.1 | **77.9%** | Long-horizon SWE; 9to5Google cites Claude Opus 5.5 at **74.2%** and GPT-6 Astra at **74.1%** AutomationBench (Zapier) | **51.3%** | Google claims **#1** LVBench (long video) | **91.7%** | Google claims **SOTA** CWE-bench v1 | **68%** | Google claims **tied for first** (vuln remediation) Google also points to leading placement on the Vals Index and strong domain results on Vals Finance Agent v2 and Harvey’s Legal Agent Benchmark. Orientation only: different benches measure different jobs. Your golden set still wins. ### Internal Google anecdotes (vendor examples, not your SLA) Capability _hints_ , not SLAs: quantum subroutine optimization (**40%** better than a published baseline in one example); fleet memory work freeing **300+ TiB** ; CRust migrations from **re2** / **libgav1** up to **800K+** lines for Fuchsia Zircon (under heavy audit); and a **libgav1** Rust SIMD rewrite claimed **2.7×** faster than the prior Rust port with identical video output. Cyber angle: Argon is trained for defense; Wiz’s Scan for Good is cited for a critical healthcare exposure previous frontier models missed. Vendor narrative — not an independent pen-test for compliance. ## What builders should do _this week_ OpenAI shipped **GPT-6.1 Sol** on September 29 at the same sticker band (**$2 / $10**) and it is **already** in the API and GitHub Copilot per OpenAI and GitHub’s changelog. That contrast is actionable: do not stall shipping while Fairwind widens. 1. **Keep shipping** on models you can call today: GPT-6.1 Sol, Claude Opus / Sonnet 5.5, Grok where it fits. 2. **Prepare long-horizon SWE evals** now — multi-file edits, flaky tests, migration-style tasks. When Argon’s model ID lands, you want a 2050 trajectory harness ready. 3. **Watch for the public model ID** and paid API / Ultra notes. No ID → no production default. 4. **Do not** block a release on Fairwind-only access unless you are in that program. 5. **Price for the post-intro column** ($4/$20) in any Argon ROI slide; assume cache misses until you measure them. 6. **Security posture:** if you ever get a no-guardrail cyber build, isolate it. Fairwind is defense capability plus staged safeguards not “same sandbox as the public chatbot.” ## When Argon might become your default (once the API lands) Only after a callable model ID and billing access: 1. Workloads are **long-horizon** and you are hitting today’s completion caps. 2. A **golden eval** shows Argon beating your current default on _your_ failures — not DeepSWE screenshots alone. 3. Cost model survives **post-intro** $4/$20 _and_ realistic cache hit rates. 4. Prompt-injection / tool-exfiltration tests pass under your threat model (Google claims Gray Swan IPI leadership — verify on your agents). 5. You can **rollback** to Sol / Opus / Sonnet without rewriting orchestration. Until then, Argon is a roadmap signal. Treat the blog as planning input; treat GPT-6.1 Sol and the Claude 5.5 pair as this week’s shipping surface. ## Why this post exists Frontier launches now split into two products: the **capability blog** and the **availability calendar**. Argon is a serious capability claim with a Fairwind-first calendar. The durable skill is refusing to confuse them — and having harnesses, budgets, and rollbacks ready for the day a public model ID appears. _Byline:_ YongBo Yu — Toronto AI engineer (agents, LLM workflows). GitHub: YongBoYu1.

Google on Wednesday announced its latest frontier artificial intelligence (AI) model, Gemini 4 Argon, that it said is being rolled out to a set of trusted cyber defenders through its Fairwind Program. "It delivers frontier performance in complex workflows across real-world software engineering, enterprise knowledge work like legal and finance, and cybersecurity defense," Koray Kavukcuoglu,

Google, Gemini model ailesinin yeni neslini temsil eden Gemini 4 Argon modelini duyurdu. Şirketin yeni amiral gemisi yapay zeka modeli olan Argon; yazılım geliştirme, kurumsal bilgi çalışmaları ve siber güvenlik gibi karmaşık iş yüklerine odaklanıyor. Google, modeli ilk aşamada geniş çaplı olarak kullanıma açmak yerine seçili siber güvenlik ortaklarına sunmayı tercih etti. Google DeepMind Kıdemli Başkan Yardımcısı ve baş yapay zeka mimarı Koray Kavukcuoglu,

Google on Wednesday announced its latest frontier artificial intelligence (AI) model, Gemini 4 Argon, that it said is being rolled out to a set of trusted cyber defenders through its Fairwind Program. "It delivers frontier performance in complex workflows across real-world software engineering, enterprise knowledge work like legal and finance, and cybersecurity defense," Koray Kavukcuoglu,

Koray Kavukcuoglu, a longtime lieutenant of Demis Hassabis who took over Google DeepMind's day-to-day operations in August when Hassabis became chairman, told a conference audience last week he was encouraged by the model's performance. "I have the utmost trust in the team," he said. "In my mind, it's a certainty that we are always gonna be at the frontier." Some Google employees who have used the model say it does less well on real work, coding in particular, than its benchmark scores suggest, Bloomberg reported. Google unveiled Gemini 4 Argon on Wednesday, initially for selected cybersecurity partners, with leading scores on several software engineering and professional-work benchmarks. Argon scored 53 on the Artificial Analysis Intelligence Index, level with OpenAI's GPT-6 Astra and Anthropic's Claude Fable 5.1 and trailing Anthropic's newest models. The Breakdown * Google unveiled Gemini 4 Argon on Sept. 30, first only to cybersecurity partners in its Fairwind program; paid API customers and Google AI Ultra subscribers are next, with no date. * Argon scored 53 on the Artificial Analysis Intelligence Index, level with GPT-6 Astra and Claude Fable 5.1 and behind Claude Opus 5.5 (58) and Claude Sonnet 5.5 (56). * Some Google employees with direct access say it struggles with certain coding tasks, including front-end design, and two people said it appears affected by "benchmaxxing." * Google said it would be inaccurate to say the model underperforms in coding; one employee cited "large consensus" that Argon is at the frontier. AI-generated summary, reviewed by an editor. More on our AI guidelines. ## The doubts inside Google Employees with direct access to Argon said it struggled with certain coding tasks when they put it to work. One person singled out front-end design, the work that determines how an app or website looks and feels. Some employees believed Anthropic's Fable and OpenAI's Astra models were improving faster than Gemini and that Gemini 4, even at its best, would still lag behind those models in some areas. Others thought Google had caught up. Alphabet shares rose about 1.7% in extended trading after the announcement; late in regular trading they had pared the day's earlier gains after the report on employee skepticism appeared. Two people familiar with Argon said it appeared affected by "benchmaxxing." Experts describe this as concentrating engineering effort on getting a high test score, with less attention to whether the resulting product does the user's job well. They say labs prioritize those scores because customers often judge models by benchmark rankings. Edwin Chen, founder of the AI startup Surge AI, described how reliance on benchmarks generally could lead a lab to produce code in a particular programming language while giving less attention to whether the finished app was easy to use or well designed. "An analogy would be, 'Oh yeah, my kid got a really good score on the SAT', but the SAT doesn't translate into real-world performance," Chen said. "It's an incredibly pernicious problem." FREE · ABOUT FIVE MINUTES Track the frontier model race as it shifts. Implicator cuts the flood to the developments worth your attention, with concise reporting on what changed and why it matters. Delivered every weekday at 4:45 a.m. Pacific, 7:45 a.m. Eastern. Email address Get the free briefing Check your inbox for the confirmation link. From San Francisco. No spam. Unsubscribe anytime. ## Google's case The employees describing Argon's shortcomings were anonymous. Google disputed their account, saying it would be inaccurate to say the model underperformed in areas such as coding. An employee familiar with model development said there was "large consensus" internally that Argon was at the frontier, cited rigorous testing and denied difficulties with messy, real-world coding tasks. Tulsee Doshi, who leads Gemini products at DeepMind, said, "We've seen strong performance up close as Googlers have put the model through its paces in recent weeks, with many relying on it for their hardest coding and research problems." Google's launch announcement offered an example from its libgav1 video decoder. Argon agents replaced 32,000 lines of SIMD code in an existing Rust port. Google said the resulting decoder ran 2.7 times faster than that earlier Rust version with identical video output. A person familiar with the matter said the model stood out at making sense of inputs beyond text, such as extracting metadata from video, and cited its safety, cybersecurity and ability to communicate clearly and naturally. ## What the independent tests show On the Artificial Analysis Intelligence Index, Argon at its highest available reasoning setting scored 53 points, matching GPT-6 Astra and Claude Fable 5.1. Claude Opus 5.5 scored 58 and Claude Sonnet 5.5 scored 56. Google's previous non-Flash model, Gemini 3.1 Pro Preview, scored 30 on the same index. Artificial Analysis described Google as "one of the top three labs in intelligence achieved." Coding rankings varied by test. In Google's launch comparison, Argon scored 77.9% on DeepSWE v1.1, which measures long-horizon software engineering, against Claude Opus 5.5's 74.2% and GPT-6 Astra's 74.1%. Across the 18 benchmarks Google disclosed, Argon led outright on 12 and tied for first on another. On Artificial Analysis's Terminal Bench 4 evaluation, Argon scored 57%, behind Claude Sonnet 5.5 at 64%, Claude Opus 5.5 at 60% and GPT-6 Astra at 59%. Know someone who'd find this useful? ✉️ Email it to a friend in one click, or they can subscribe free here. On Arena's web-development ranking, where people vote on outputs, Argon placed eighth with 1,679 points, up from 29th for Gemini 3.8 Flash. The independent results also gave Google category leads. Argon topped Text Arena's human preference ranking with 1,525 points, 20 ahead of Claude Opus 4.6. It placed first on the Vals Index at 68.9%, becoming the first Gemini model to lead that measure of professional work. The Vals ranking also puts Anthropic's mid-tier Claude Sonnet 5.5 above its top model, Claude Opus 5.5, a quirk to treat with caution. ## A year of catching up Last November, Google debuted Gemini 3, a well-received model widely seen as a turning point in its efforts to keep up with OpenAI and Anthropic. Google announced Gemini 3.5 Pro at I/O in May, promised it for June and then abandoned it. Argon is its first proprietary model above the Flash class in more than seven months. Training runs to build such a model can cost as much as $400 million, according to Mandeep Singh, an analyst at Bloomberg Intelligence. Google's worries about AI coding predate Argon. In April, three former employees said some DeepMind teams, including teams working on Gemini, used Anthropic's Claude Code. Kathy Korevec, who oversaw Google's Jules coding tool before leaving for OpenAI that month, described fragmented, overlapping developer tools in a post on X. "That's not a talent problem. It's a systems problem," she wrote. ## Who can use it Most developers cannot yet test Argon against their own work. Initial access is through Google's Fairwind cybersecurity program, and the company is participating in the U.S. government's voluntary pre-release model access process. Paid API customers and Google AI Ultra subscribers are next in line. Google has given them no release date, saying access will come "as soon as possible." Frequently Asked Questions What is Gemini 4 Argon? Gemini 4 Argon is Google's new flagship AI model, unveiled on Sept. 30, 2026. It is Google's first proprietary model above the Flash class in more than seven months, after the company announced Gemini 3.5 Pro in May, promised it for June and then abandoned it. How does Argon compare with OpenAI and Anthropic models? On the Artificial Analysis Intelligence Index, Argon scored 53, matching GPT-6 Astra and Claude Fable 5.1, while Claude Opus 5.5 scored 58 and Claude Sonnet 5.5 scored 56. On Terminal Bench 4 it scored 57%, behind Sonnet 5.5, Opus 5.5 and GPT-6 Astra. It leads Text Arena with 1,525 points and the Vals Index at 68.9%. What are Google employees saying about Argon? Anonymous employees with direct access said it struggled with certain coding tasks when they put it to work, and one singled out front-end design. Some believe Anthropic's Fable and OpenAI's Astra models are improving faster and that Gemini 4 will still lag behind them in some areas. Others think Google has caught up. What is benchmaxxing? Experts describe benchmaxxing as concentrating engineering effort on getting a high test score, with less attention to whether the product does the user's job well. They say labs do it because customers often judge models by benchmark rankings. Two people familiar with Argon said it appeared affected. When can developers use Gemini 4 Argon? Initial access runs through Google's Fairwind cybersecurity program, and Google is participating in the U.S. government's voluntary pre-release model access process. Paid API customers and Google AI Ultra subscribers are next in line, but Google has given no release date beyond "as soon as possible." AI-generated summary, reviewed by an editor. More on our AI guidelines. ## Related stories Hassabis Steps Aside at Google DeepMind, Jeff Dean ExitsDemis Hassabis is handing over day-to-day control of Google DeepMind, and Jeff Dean is leaving after 27 years to run a startup Google is investing in. Alphabet shares fell more than 5%, a reading that sits awkwardly beside the company's own account of the day.Implicator.aiGemini 3.8 Flash Scores 59, Trails Fable and SolGoogle’s Gemini 3.8 Flash sits two index points behind GPT-5.6 Sol and seven behind Claude Fable 5.1, but costs less per measured task. Open-weights GLM is cheaper, and the Cyber model’s external cost is still missing.Implicator.aiGemini Hits 950 Million Users as Alphabet Burns CashAlphabet said the Gemini app reached 950 million monthly active users, up from about 650 million last October. The same quarter brought its first negative free cash flow since 2004, a capital-spending forecast of up to $205 billion, and a CEO defending a delayed flagship model.Implicator.ai

Google will withhold its most powerful AI model from the public SAN FRANCISCO (UNITED STATES) - Google on Wednesday said it would withhold its most powerful artificial intelligence model from the public for now, releasing Gemini 4 Argon only to a vetted group of cybersecurity experts to avoid misuse by hackers. "Safely releasing frontier capabilities at this level requires a phased approach," wrote Koray Kavukcuoglu, Google's chief AI architect, in a blog post announcing the model.

Gemini 4 Argon 소개 Google이 2026년 9월 30일 새 프런티어 모델 Gemini 4 Argon 을 공개했습니다. 긴 호흡의 다단계 작업을 끝까지 수행하도록 만든 모델로, 출력 토큰 한도를 기존 64K에서 1M으로 늘렸고 소프트웨어 엔지니어링, 법률과 금융 같은 전문 업무, 사이버 보안 방어 영역의 벤치마크에서 1위를 주장합니다. 다만 이번 발표는 일반 출시가 아니라 공개 순서를 먼저 밝힌 발표 에 가깝습니다. 첫 사용자는 개발자가 아니라 Fairwind Program으로 선정된 사이버 방어 기관들입니다. Google은 이 순서를 택한 이유를 안전성에서 찾습니다. 발표를 쓴 Google DeepMind의 Koray Kavukcuoglu는 이 수준의 능력을 안전하게 내놓으려면 단계...

Alphabet Inc.’s Google has begun rolling out Gemini 4 Argon, its long-awaited flagship artificial intelligence model, but the company is grappling with internal skepticism over how well it performs in...

Google on Wednesday said it would withhold its most powerful artificial intelligence model from the public for now, releasing Gemini 4 Argon only to a vetted group of cybersecurity experts to avoid misuse by hackers. “Safely releasing frontier capabilities at this level requires a phased approach,” wrote Koray Kavukcuoglu, Google’s chief AI architect, in a […] The post Google restricts access to new AI model over safety concerns appeared first on Digital Journal.

Google today revealed its next AI frontier model, which it’s calling Gemini 4 Argon. The new model delivers “frontier performance in complex workflows across real-world software engineering, enterprise knowledge work like legal and finance, and cybersecurity defense,” according to chief AI architect and Google DeepMind SVP Koray Kavukcuoglu. But the company is limiting access at first to a “set of trusted cyber defenders,” and Kavukcuoglu says that Google is “actively engaged in the U.S. government’s voluntary process for pre-release model access while we gradually expand access.” Kavukcuoglu says Gemini 4 Argon is already powering Google’s “internal workflows,” highlighting how the model has helped with tasks like large-scale codebase migrations. Google also shared a big chart showing many benchmarks where Gemini 4 fares better than competing models from OpenAI and Anthropic. (The AI community was buzzing earlier this week on X over what appeared to be leaked benchmarks for the new model.) Google will be strengthening “critical frontier safeguards” before a broader rollout, including defending against misuse and prompt injection attacks and monitoring for misalignment. The launch of Gemini 4 Argon comes just a day after OpenAI’s splashy DevDay conference, where OpenAI launched its Dots AI agent and GPT-6.1 Sol AI...

Google DeepMind’ın başındaki isim Koray Kavukçuoğlu, geçtiğimiz hafta The Information’a verdiği röportajda Gemini 4 model ailesi için son rötuşlarının yapıldığını ve şirketin seriyi yıl sonundan önce piyasaya sürmeyi hedeflediğini aktarmıştı. Bekleyişi bugün itibarıyla bitiren ve yeni amiral gemisi yapay zeka modeli Gemini 4 Argon’u duyuran Google, kağıt üzerinde oldukça iddialı model hakkında yaptığı resmi açıklamada, “Argon, Fairwind Programımız kapsamında güvenilir siber güvenlik uzmanlarından oluşan belirli bir gruba sunulmaya başlanıyor. Karmaşık ve uzun soluklu iş akışları boyunca derin akıl yürütme yeteneğini sürdürebilecek şekilde geliştirilen Argon, Google’da şimdiden çalışma ve ürün geliştirme biçimimizi temelden değiştirdi. Yeni modelimiz kodlama/ yazılım mühendisliği süreçleri, hukuk ile finans gibi kurumsal işler ve siber güvenlik savunmasını kapsayan karmaşık iş akışlarında en ileri düzey performans sunuyor.” ifadelerine yer verdi. Birçok testte GPT-6 Astra, Claude Fable 5.1 ve Claude Opus 5.5’i geride bırakmayı başaran Argon, henüz geniş çaplı olarak herkese açılmıyor. Bu konuda Google’ın paylaşımı şöyle: “Argon’u kodlama, kurumsal […] Google, yeni üst seviye yapay zeka modeli Gemini 4 Argon’u duyurdu yazısı ilk olarak Teknoloji haberleri - LOG üzerinde yayınlandı.

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Google se acerca al lanzamiento de Gemini 4, su próximo modelo de IA, después de haber quedado rezagado frente a la competencia. El nuevo responsable de DeepMind, Koray Kavukcuoglu, indicó que el modelo está en fase de refinamiento y que la compañía planea sacarlo antes de fin de año. El objetivo es

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