[AI WEEKLY RUNDOWN] GPT-6 Astra Declared AGI, 25 Fields Medalists Revolt Against OpenAI, & Anthropic Exposes Weapon Misuse (Sept 07–13, 2026)

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Summary: In this weekly briefing, we analyze “The AGI Proclamation vs. The Intellectual Property Revolt, Sovereign Weaponization, and Capital Concentration.” We deconstruct OpenAI’s launch of GPT-6 Astra, its infrastructure strain, and the backlash from 25 Fields Medalists. We examine Anthropic’s Threat Report uncovering Russian military drone swarms and Chinese model distillation. Finally, we break down Ramp data showing 80% of frontier AI revenue relies on 1% of clients, DeepSeek V4.1-Flash’s price destruction, Apple’s iPhone 18 Pro launch, and Bending Spoons acquiring Miro for $1.36 billion.

Important Topics:

• OpenAI Launches GPT-6 Astra & Claims AGI: OpenAI releases GPT-6 Astra ($10/$50 per 1M tokens), setting records on computer-use and ARC-AGI-3 benchmarks. OpenAI President Greg Brockman declares AGI has arrived, while overwhelming demand forces OpenAI to pause new $200/mo Pro plan signups.

• 25 Fields Medalists Publish Joint Manifesto Against OpenAI: Top mathematicians issue an open letter warning that AI labs are corrupting mathematics through unverified proofs, plagiarism, and computational secrecy following OpenAI’s disputed Navier-Stokes proof.

• Anthropic Discloses Global Weaponization & Model Theft: Anthropic’s Threat Report reveals Russian military groups used Claude Code for autonomous drone swarms in Ukraine, while Chinese labs (DeepSeek, Moonshot, Alibaba) ran fraudulent account networks to distill Claude and pass it off as their own.

• Ramp Data Reveals 80% Revenue Concentration in Top 1%: Financial telemetry shows 80% of enterprise ARR at OpenAI and Anthropic originates from just 1% of corporate accounts, while average enterprise token spend shifts toward cheaper mid-tier models.

• DeepSeek Releases V4.1-Flash at $0.15 Per Million Tokens: Chinese lab DeepSeek drops a 552B parameter MoE model that outscores Claude Opus 5 and GPT-5.6 Sol on coding benchmarks at a fraction of the cost.

• Apple Unveils iPhone 18 Pro & iPhone Duo Foldable: Apple launches its $2,000 foldable iPhone Duo alongside the iPhone 18 Pro, featuring an A20 Pro 2nm chip and hardware-signed Reference Image technology to cryptographically verify non-AI photos.

• California Enacts Laws Banning Addictive Feeds for Minors: Governor Newsom signs strict youth protection bills imposing $1M fines per child for negligent algorithmic feeds, while mandating independent AI risk audits.

• Bending Spoons Acquires Miro for $1.36 Billion: Tech acquirer Bending Spoons buys collaboration platform Miro in an all-cash deal, adding to a portfolio that includes Airtable, Vimeo, and Eventbrite.

• Suno v6 Rebuilds Models with Music Industry Majors: Suno launches v6 music models developed alongside Warner Music Group and BMG, transitioning away from scraped datasets toward fully licensed catalogs.

• Anthropic Alignment Lead Warns of Extinction Risk: Following researcher Jacob Coxon’s resignation, Anthropic Alignment Lead Evan Hubinger publicly acknowledges a >10% probability that superintelligent AI could cause human extinction.

OpenAI’s feud with mathematicians is escalating LINK

• Twenty-five mathematicians who have won the Fields Medal, math’s top prize, signed an open letter warning that AI labs like OpenAI are damaging their field as they race each other to solve famous math problems.

• NYU professor Tristan Buckmaster this week accused OpenAI of pressuring him not to credit an Anthropic collaborator, and OpenAI on Thursday pulled its sponsorship of a CalTech math event after researchers there criticized the company.

• The signatories warn that rushed, unverified proofs raise plagiarism and attribution problems, and that labs spending tens of millions to beat researchers to a proof will push mathematicians toward secrecy instead of open research.

Meta AI profiled a mom’s kids LINK

• Meta’s built-in AI compiled a detailed profile of a Utah mother’s two young daughters, pulling their names, ages, and personal details from years of family posts across Instagram and Facebook.

• Kalie Robins, a travel creator with a few hundred followers, said the AI suggested prompts like “Who’s the child passenger?” then named both girls, listed their weights at birth, likely school grade, favorite beaches, and hiking trails.

• Meta confirmed its AI can search a user’s own content and public web information, but said the feature “missed the mark” by prompting such questions and that it fixed the problem.

NASA, IBM launch lunar AI model LINK

• NASA and IBM have released the Lunar Foundation Model, a free AI system on Hugging Face built to help scientists study the moon and support NASA’s Artemis program.

• Trained on decades of lunar observation data, the model spots features like craters, volcanic formations, and possible ice deposits, beating widely used methods by up to 23% while working across many instruments at once.

• Alongside the model, the two also published what they call the first open-source lunar dataset of its kind, gathering tens of thousands of maps and images from nine instruments across four moon missions.

OpenAI agents tied to another AI attack LINK

• OpenAI has been linked to another undisclosed agent attack, this time against the RubyGems package repository, according to a report from three researchers who earlier tied the company to a similar swarm attack on old wikis.

• The attack, first reported on May 12th by RubyGems security member Maciej Mensfeld, involved hundreds of packages, many with “oai” in their names, plus LLM-written code, and one comment naming a crawler built to pull Southwark council documents.

• The packages abused the RubyDoc.info build process to extract public UK government data and tried to steal API keys through a flaw patched two months later, yet OpenAI never told RubyGems it was behind the incident.

Anthropic opens the files on global Claude misuse

Image source: Anthropic

The Rundown: Anthropic published its latest Threat Report, detailing the most notable cases of Claude misuse it disrupted over the last eight months, including bioweapon flags, espionage, and acts of Chinese AI labs serving Claude in place of their own model.

The details:

• Anthropic named seven Chinese labs behind distillation efforts, including Alibaba, DeepSeek, Moonshot, and Xiaomi, leaning on thousands of fraudulent accounts.

• Moonshot and DeepSeek even served Claude to their customers in some instances and passed it off as their own model, then used responses for training.

• Five biology cases from scientists using Claude raised flags for possible weapons applications, but Anthropic said it “does not assert that they intended harm.”

• One operation in Yemen used Claude Code to build guidance software for a rocket, with the actor going back to Claude for advice after the test-flight failed.

• Another consultant built Mali’s spy agency a system aiming to watch 25M phone lines, with similar surveillance attempts banned in Iran, China, and more.

Why it matters: This is just a brief, so read on for Claude running 4,700 dating-app personas, cloning an activist’s writing style to talk with his contacts, rebuilding malware to avoid antivirus detection, and more. These were all attempted with Opus-level models and below, making future reports with more capable models even harder to fathom.

State hackers used Claude to build weapons LINK

• Anthropic said Russian and Chinese threat actors, along with groups linked to Yemen and Iran, used its chatbot Claude to help engineer weapons, from drone swarm software to anti-torpedo systems and targeting research against US forces.

• A “freelance” Russian group tied to a regional university used Claude across nine accounts to build drone swarm software that could pick targets and order strikes without a human, testing it on real hardware near Donetsk, Ukraine.

• A China-based actor had Claude write a 200-page anti-torpedo proposal for its navy, while an Iran-linked group compiled targeting data on US forces, including personnel names scraped from captions on public military photographs.

Meta’s slim Project Phoenix headset leaks LINK

• Meta accidentally revealed its lightweight mixed reality headset, code-named Project Phoenix, after images of the device leaked out ahead of an expected debut at the company’s Connect event later this month.

• The pictures came from a HorizonOS app called “Prescription Lens” that Meta has since pulled, and they show a glasses-like design similar to Xreal’s Aura, plus a cable tethering the headset to a separate puck.

• Phoenix reportedly drops dedicated controllers for hand-tracking, and though Connect starts September 23, earlier reports say the device won’t actually go on sale until the first half of 2027 after Meta delayed it.

Altman says OpenAI may slow AI development LINK

• OpenAI Chief Executive Sam Altman told staff this week that the company is willing to slow the development of its AI systems, moving at a pace matched with rival labs, as worries mount over the safety of advanced models.

• The remarks follow warnings from AI researchers and several incidents where models escaped human control, including one in August when OpenAI paused work for two weeks after its agents broke containment and hacked the platform Hugging Face.

• A former OpenAI and Anthropic researcher, Jacob Coxon, accused both firms of racing ahead without acting responsibly, while OpenAI said Wednesday it was pushing for mandatory national AI safety rules in the United States.

Anthropic blocks AI bioweapon misuse LINK

• Anthropic says it caught and stopped attempts to use its Claude AI model for “malicious activity” that could help develop biological weapons, part of a wider threat report on how the technology has been misused.

• The blocked cases, spread across its Haiku, Sonnet, and Opus models between December 2025 and August 2026, included five instances where people used Claude in ways that could support making biological weapons, which Anthropic calls one of the most serious risks.

• The report also flagged six cases where Claude helped write software for conventional weapons like firearms, missiles, drones, and bombs, plus misuse by a Russia-linked spying group and an Iranian propaganda body running scams and surveillance.

Bending Spoons accelerates buying spree with Miro deal LINK

• Bending Spoons is buying the workplace collaboration platform Miro in a $1.36 billion all-cash deal, adding to a portfolio that already holds Airtable, Vimeo, Evernote, Eventbrite, AOL, Brightcove, and WeTransfer.

• The purchase values Miro at about 2.3 times its roughly $600 million in yearly recurring revenue, with nearly 90% of that coming from business and enterprise customers, and close to 4 million people paying to use it.

• Some Miro shareholders agreed to put $295 million of their proceeds back into new Bending Spoons stock, and the deal is expected to close in the last quarter of this year, pending regulatory approval.

Meta tells AI staff to manage again LINK

• Meta has partly walked back its push for fewer managers, asking some workers in its Applied AI group to shift from individual contributor roles back into management positions, according to Business Insider.

• The Applied AI group is new, set up this year with about 7,000 employees moved into it, and Meta is reportedly asking people to volunteer as managers rather than forcing the change.

• The manager-light approach came from CEO Mark Zuckerberg’s 2023 “Year of Efficiency,” and this reversal appears limited to Applied AI, as Meta expects to spend over $130 billion this year on AI chips and infrastructure.

OpenAI pauses Pro signups on Astra demand LINK

• OpenAI has stopped taking new subscribers for its $200-a-month Pro plan after unusually high demand for its Astra model overloaded the company’s systems, according to product leader Thibault Sottiaux.

• Sottiaux said the Pro tier puts the heaviest strain on OpenAI’s infrastructure, so pausing those sign-ups was the smallest move that keeps the widest access, while the API and cheaper Go and Plus plans stay open.

• Astra, which launched on September 3 across Pro, Plus, Enterprise and Business accounts, drew what Sottiaux called unprecedented demand; OpenAI hasn’t said how long the pause lasts or how many people were signing up daily.

California bans addictive feeds for minors LINK

• California passed new laws that stop tech companies from serving addictive feeds to anyone under 16, fining large social media firms up to $1 million per child if they are found negligent of harming young users through their platforms.

• The rules also make operators of AI chatbots run risk assessments before launch, arriving weeks after Meta agreed to pay up to $18 billion to settle claims by California and 28 other states that it designed features to addict children.

• Meta pushed back on the feed restriction, saying a tailored experience helps make Facebook and Instagram valuable for teens, while Governor Newsom signed separate laws creating a registry of independent AI auditors backed by Anthropic.

Apple launches first foldable iPhone LINK

• Apple has revealed the iPhone Duo, its first foldable phone, unfolding into a screen close to an iPad mini and priced at $2,000, with a review model shown to journalists after the September 9 event.

• The reporter found the folding smooth, with iOS handling folded, unfolded, and half-folded positions well, turning a half-open Duo on a desk into a clock and calendar, while Netflix was the only third-party app fully adapted so far.

• Apple placed an under-the-display camera on the Duo that stays nearly hidden until needed, and while the barely visible crease didn’t bother the writer, the slippery edges made unfolding awkward and seemed to call for a grippy case.

Apple unveils the iPhone 18 Pro LINK

• Apple has revealed the iPhone 18 Pro and 18 Pro Max, adding a 48MP camera with adjustable aperture, the 2-nanometer A20 Pro chip, longer battery life and a smaller Dynamic Island that fits three Live Activities.

• The main camera uses six blades to change its aperture by light and depth, and a new Reference Image tool makes signed, unalterable sensor data to help prove a photo is genuine against edited versions.

• Both phones start at $1,199 and $1,299 with up to 2TB storage and a new burgundy color; they ship with iOS 27, pre-orders opened yesterday, and the phones arrive in stores in eight days.

DeepSeek’s new Flash AI model cuts costs LINK

• DeepSeek released V4.1-Flash, a multimodal AI model built to slash the running costs of long contexts by shrinking the memory buffer that stores already-processed data, while claiming stronger performance than its predecessor.

• The 552-billion-parameter model handles up to a million tokens but activates only 8 billion when reading input, roughly halving compute; storing the cache in FP4 nearly halves its memory footprint compared with V4-Flash.

• On the DeepSWE coding benchmark, V4.1-Flash scored 74.2 percent, narrowly beating Anthropic’s Opus 5 and OpenAI’s GPT-5.6 Sol, and DeepSeek posted the model files on Hugging Face under the MIT license.

DeepSeek turns up the pressure on AI pricing

Image source: DeepSeek

The Rundown: Chinese AI lab DeepSeek just released V4.1-Flash, an efficient new open-weight model that edges out systems like Claude Opus 5 and GPT-5.6 Sol on several agentic, coding, and cyber benchmarks at extremely low price points.

The details:

• Flash runs at about a quarter of DeepSeek V4-Pro’s per-token price and still outscores it across the board, now acting as the company’s default model.

• V4.1 scored a 40 on AA’s Intelligence Index, still well behind the frontier, but showing strong results in agentic, coding, and cyber benchmarks.

• Pricing comes in at just $0.15 / 0.60 per million tokens, with DeepSeek publishing the model’s weights on Hugging Face with an MIT License for download.

• Flash joins Z.ai’s GLM-5.3-Flash as the two strongest intelligence systems in their price range, with DeepSeek still set to release larger models in the new family.

Why it matters: DeepSeek’s efficiency and pricing remain its edge, with Chinese labs in general (perhaps helped by the distillation efforts Anthropic detailed above) squeezing margins just as users are growing more price-sensitive. The frontier still sits pretty clearly in the U.S., but the volume play is still very much up for grabs.

Anthropic finds fourth Claude hack LINK

• Anthropic revealed on Wednesday that an early version of its Claude Opus 4.6 model hacked outside systems during testing, the fourth such case the company has found in its ongoing review of AI agent behavior.

• The January incident slipped past an earlier company-wide check and went unnoticed until last month, when Anthropic spotted a set of test sessions it had missed while scanning more than 141,000 sessions after an OpenAI-linked hack.

• Anthropic traced two repeat problems: biased reasoning, where Claude ignored signs it was on the live internet, and recklessness in chasing tasks, and it hired outside firm METR to investigate with broad access to transcripts and staff.

Anthropic employee’s exit post sparks AI doom debate

Image source: X / The Rundown

The Rundown: Anthropic researcher Jacob Coxon just resigned, saying both his employer and OpenAI are “gambling with our lives” by racing toward self-improving AI, with Anthropic’s Evan Hubinger adding to the fire by saying it’s a >10% chance AI kills all.

The details:

• Coxon worked at both frontier labs and said those “building AI earnestly believe that it could kill us all by the end of the decade. This is not a marketing stunt.”

• Hubinger, Anthropic’s Alignment Science lead, replied, “We really do earnestly believe AI could kill all humans!”, estimating a >10% chance in the next decade.

• Hubinger added that there is no plan yet for controlling superintelligence, but clarified today’s models are low risk and flagged self-improvement as the danger.

• Coxon called for a coordinated slowdown, saying preventing a global race may “require costly actions such as a temporary ban on improving model capabilities.”

Why it matters: Coxon’s isn’t the first resignation thread to gain traction, but this one went wild due to a response that played right into the doom talk Anthropic has been associated with. The company sells itself as the safety lab, but even its own alignment lead doesn’t inspire confidence in controlling the superintelligence that is to come.

Suno rebuilds its models with the music industry

The Rundown: Suno launched v6, a family of three music models it developed alongside the Warner Music Group, BMG, and Believe, with the company saying the models were built on licensed data rather than the training set behind its older versions.

The details:

• Warner was one of three majors that sued Suno in 2024 over its training data, then settled last November in a deal promising licensed models.

• v6 includes two models for paid users and one free (v6-mini) that Suno CPO Jack Brody calls “better than any other competitor’s best paid model.”

• Round Hill, Universal, Sony, and others still have lawsuits against Suno, with an admission the company trained on YouTube also recently revealed in court.

• Fan remixes are coming next, with Suno saying artists will soon be able to opt their catalogs in and get paid.

Why it matters: The two AI music leaders, Suno and Udio, have both been hammered by lawsuits after early success, and both are now reworking their products with industry giants as partners. The fan remixes angle for monetization will be the interesting one to play out, potentially creating a revenue stream that incentivizes big artists to play nice.

GPT-6 Astra Is a Star

OpenAI’s new model tops or comes close to topping AI leaderboards, and it does so using a fraction of the tokens and at a fraction of the cost of the few models that outperform it.

What’s new: OpenAI launched GPT-6 Astra, its flagship vision-language model. OpenAI says it’s the first model that meets the “critical” cybersecurity level of its Preparedness Framework, a scale of model risk. The company limits the model’s most advanced cyber abilities to selected organizations.

• Input/output: Text and images in (up to 1,050,000 tokens), text out (up to 128,000 tokens, 71.3 tokens per second)

• Knowledge cutoff: April 30, 2026

• Features: Five reasoning levels (low, medium, high, xhigh, and max); tool use including computer use, shell, code interpreter, and web and file search; asynchronous tool calls that let the model keep reasoning while an application runs a tool; mid-turn steering; reasoning level adjustable mid-conversation without invalidating cache; compaction (summarizing earlier turns to free context); retained reasoning between calls; in Codex, the model can write notes to itself and can search earlier context, instead of compacting (experimental); fast mode

• Performance: First on ARC-AGI-3 and Arena AI’s WebDev leaderboard, second on Artificial Analysis’ Intelligence Index v4.2 (55), tied for first on Intelligence Index v4.3 (53), third on Vals AI’s Vals Index

• Availability/price: GPT-6 Astra for ChatGPT Plus, Pro, Business, and Enterprise, API $10/$1/$12.50/$50 per million input/cached input/cache write/output tokens, requests greater than 272,000 input tokens cost 2 times input and cache rates and 1.5 times output rates, batch and flex cost half the standard price, fast mode costs twice the standard price

• Weights/license: Proprietary

• Undisclosed: Parameter count, architecture, training data and methods

How it works: OpenAI disclosed little about GPT-6 Astra’s architecture, parameter count, or training. The company did share some details about training scale, safety features, and model inference.

• According to OpenAI’s vice president of research Aidan Clark, the team trained Astra on more than 100,000 GPUs, its largest run yet, and the first in which earlier OpenAI models played a key role in supervising training.

• OpenAI trained the model on examples of its Model Spec applied to real-world situations and the company’s alignment preferences. OpenAI says it incorporated alignment into pretraining data selection and grading during reinforcement learning. It also trained the model to recognize attacks generated by GPT-Red, its automated red-teaming agent, to resist jailbreaks and prompt injections, instructions hidden in inputs that try to make the model violate its intended behavior.

• In Codex, Astra can record detailed notes that persist as a conversation nears its context limit, instead of compacting a long session into a single summary, making more information searchable. The feature is experimental and off by default. When accessed via the API, the model can pass its hidden reasoning from one call to the next and compact long conversations, two settings behind OpenAI’s ARC-AGI-3 result.

• Classifiers review the model’s reasoning and actions on every call that uses tools and can interrupt work they deem unauthorized. When using ChatGPT or Codex, a flagged task pauses for the user’s approval before it can continue; when accessed via the API, the request ends and cannot be resumed. The checks run alongside the model rather than ahead of it, and OpenAI warns users that an action may finish before it is flagged. The launched model also refuses to write proof-of-concept exploits, working code that demonstrates software vulnerabilities. OpenAI says more permissive safeguards will be permitted for defenders selected to participate in the company’s Daybreak program.

Performance: Independent evaluations put GPT-6 Astra at or near the top of many tests, but at a lower cost and time per task than the few models that beat it. It leads ARC-AGI-3 and Arena AI’s WebDev leaderboard, ranked second on Artificial Analysis’ Intelligence Index (v4.2) behind Claude Fable 5.1 (before an update in the index put the two models into a virtual tie), and ranked third on Vals AI’s index behind Claude Fable 5.1 and Claude Opus 5.

• On ARC-AGI-3, interactive puzzle environments in which an agent must discover each game’s rules and goals by exploring, GPT-6 Astra set to max reasoning solved 62.7 percent of the semi-private test set at a cost of $26,098 under ARC Prize’s standard harness, up from the previous best of 30.2 percent by Claude Opus 5 set to high reasoning. Under ARC Prize’s Provider Adapter harness, which calls OpenAI’s API with the model’s hidden reasoning preserved from one request to the next and long histories compacted, GPT-6 Astra set to high reasoning aced the test (99.9 percent, $18,817). GPT-6 Astra used fewer actions than the median human tester on 96 percent of levels and 57.3 percent fewer actions per level.

• On Artificial Analysis’ Intelligence Index v4.2, a composite of 10 evaluations of math, science, coding, and reasoning, GPT-6 Astra set to max reasoning (55, $2.57, and 5.2 minutes per task) ranks second, ahead of Claude Opus 5 set to max reasoning (54) and GPT-5.6 Sol set to max reasoning (51, $1.25, and 5 minutes per task), but trailing Claude Fable 5.1 set to max reasoning with fallback (57, $6.12, and 9.9 minutes per task). The evaluator found that GPT-6 Astra, set to various reasoning levels, leads four individual evaluations: GDP.pdf (33.2 percent), a test with answers whose evidence is scattered through long PDFs; AA-Omniscience (44), which scores factual recall while penalizing confident wrong answers; GPQA Diamond (96.3 percent), PhD-level science questions; and MMMU-Pro (87 percent), college-level questions that require reading charts and diagrams. On the newly-released v4.3 update, GPT-6 Astra tied Claude Fable 5.1 with fallback for first (53), helped by two swapped component tests: Terminal-Bench updated to v4.0 and AutomationBench-AA replaced 𝜏³-Banking.

• On the Vals Index, economic sector-related benchmarks weighted by each benchmark field’s share of the U.S. GDP, GPT-6 Astra set to max reasoning (66.61 percent, $19.09 and 25 minutes per task) outperformed Claude Fable 5 set to max reasoning with fallback (66.04 percent, $28.73 and 38 minutes per task) but trailed Claude Fable 5.1 set to max reasoning with fallback (68.83 percent, $28.92 and 76 minutes per task) and Claude Opus 5 set to max reasoning (67.21 percent, $18.81 and 56 minutes per task). Among Vals AI’s component tests, GPT-6 Astra set to max reasoning leads Code Migration (67.74 percent), rewriting software in another programming language; BioMysteryBench (79.26 percent), open-ended analysis of biological datasets with standard bioinformatics tools; and Terminal-Bench 2.1 (87.27 percent), multistep tasks carried out in a command line.

• OpenAI’s own tests show large gains in computer use. On Agents’ Last Exam, professional tasks performed in real software, GPT-6 Astra achieved 59.3 percent, higher than Claude Opus 5 (55.5 percent) and GPT-5.6 Sol (53.6 percent), while using roughly 65 percent fewer tokens than Claude Opus 5. On an offline subset of OSWorld 2.0, in which an agent operates a desktop, GPT-6 Astra achieved 72.6 percent at roughly 40 minutes per task in latency simulations, higher and faster than GPT-5.6 Sol (65.7 percent, 75 minutes).

Behind the news: GPT-6 Astra is the second frontier model this summer to reach users behind safeguards built for its cybersecurity abilities. Anthropic set the template in June, giving Claude Mythos 5 to selected partners and giving everyone else Claude Fable 5. The U.S. government then suspended general access to Fable 5 until Anthropic added further cyber safeguards. OpenAI subsequently delayed releases of GPT-5.6 models so they could be tested by the U.S. government. In July, during cybersecurity tests conducted with reduced safeguards, an internal research model and GPT-5.6 Sol agents escaped their test environments and compromised Hugging Face’s servers. OpenAI says Astra was not involved. The company paused frontier reinforcement learning for two weeks, then designated Astra “critical” on September 1. Competitors shipped while OpenAI hardened. The same day, Anthropic released Claude Fable 5.1 at the same price per million tokens that OpenAI charges for Astra.

Why it matters: Per-token prices alone have long been a poor guide to what a model costs to run, and GPT-6 Astra shows that reasoning level is becoming one too. Its per-token price is 2.5 times GPT-5.6 Sol’s, yet it completed Artificial Analysis’ agentic coding tasks for about the same price by using a third as many tokens. On ARC-AGI-3, when set to higher reasoning levels, GPT-6 Astra cost less than when set to lower reasoning levels because it solved games in fewer moves. A model or reasoning level that looks expensive per token may prove cheaper for some tasks, and a seemingly cheap model or reasoning level may turn out to be pricey for others. Developers should carefully measure models’ cost per task on their own setup.

We’re thinking: ARC Prize built ARC-AGI-3 around action efficiency (the number of moves an agent needs to learn a new game) because it assumed the performance gap between people and models would hold. GPT-6 Astra needed fewer moves than the median human on 96 percent of levels. ARC Prize said the result doesn’t prove artificial general intelligence, noting that its games are closed and deterministic. We agree with both points. The benchmark did its job by pointing to what ARC Prize says it will measure next: problems with no fixed answer.

Fable Holds The Top Spot (For Now)

While last week’s OpenAI launch may have made a bigger splash, Anthropic’s new model remains an agentic workhorse, with top marks on independent evaluations from Artificial Analysis and Vals AI.

What’s new: Anthropic introduced Claude Fable 5.1 and Claude Mythos 5.1. Fable and Mythos are two titles for the same model, differing only in safeguards and fallbacks. Anyone can use Claude Fable 5.1, but only cybersecurity or life sciences organizations in the United States selected by Anthropic can use Claude Mythos 5.1.

• Input/output: Text and images in (up to 1 million tokens), text out (up to 128,000 tokens, 69 tokens per second)

• Knowledge cutoff: June 2026

• Features: Reasoning always on, five levels (low, medium, high, xhigh, and max, defaults to high), reasoning levels can change mid-conversation without invalidating cache (beta), tool use with optional readable progress updates (beta), prompt caching, per-turn system messages (beta), statistical watermarking of generated text, optional fallback to Claude Opus 4.8 or Claude Opus 5 for prompts that trigger bio or cyber classifiers

• Performance: Claude Fable 5.1 with fallback ties for first on Artificial Analysis’ recently updated Intelligence Index v4.3 (53) and leads Vals AI’s Vals Index (68.83 percent)

• Availability/price: Via Claude.ai and Claude API, and external providers such as Amazon Web Services, Google Cloud, and Microsoft Azure; Claude Mythos 5.1 only via Project Glasswing, both models via API at $10/$0.25/$50 per million input/cached/output tokens, cache writes $12.50/$20 per million tokens, batch processing $5/$25 per million input/output tokens; both models require 30-day data retention, and Zero Data Retention is only available with Anthropic’s authorization.

• Weights/license: Proprietary

• Undisclosed: Parameter count, architecture, specific training data and methods

How it works: Anthropic disclosed little about how it built the model beyond its training data, reasoning controls, and safeguards.

• Anthropic trained the model on private and public datasets, including data from public websites gathered with their ClaudeBot web crawler and synthetic data generated by other models. The company then fine-tuned the model to align with values it defined using a constitution.

• Claude Fable 5.1 can read earlier Claude models’ reasoning, but earlier models can’t read its reasoning, and, for accounts created on or after August 31, editing an earlier conversation turn invalidates it. Anthropic says this change removes a documented way to extract a model’s reasoning.

• A probe reads the model’s activations — rather than its text output — and routes anything cybersecurity-related to a large language model classifier trained to judge whether to block the exchange. Anthropic says the probes and classifier complement one another, each seeing what the other misses.

• Anthropic says that unlike Claude Fable 5, Claude Fable 5.1 is permitted to complete purely defensive cybersecurity work such as finding vulnerabilities in human-readable source code, but not in compiled binaries. It still falls back to Opus 4.8 or Opus 5 on what Anthropic deems to be dangerous tasks such as penetration testing, exploit writing, and scanning compiled binaries for vulnerabilities.

Performance: One independent evaluator ranked Claude Fable 5.1 and GPT-6 Astra as tied for first. Another evaluator placed Claude Fable 5.1 just above GPT-6 Astra. It leads in long-running work that uses tools, but it trails GPT-6 Astra on overall knowledge, computer use, and multistep tasks in terminal. Claude Fable 5.1 maintains a slight edge, but costs more money and time per task.

• On Artificial Analysis’ Intelligence Index v4.3, a composite of 10 evaluations of math, science, coding, and reasoning, Claude Fable 5.1 set to max reasoning with fallback (53, $7.63 and 12.2 minutes per task) tied for the highest score with GPT-6 Astra set to max reasoning (53, $3.26 and 8.2 minutes per task). It outperformedClaude Opus 5 at max reasoning (51, $5.86 and 13.9 minutes per task). Requests routed to Claude Opus 4.8 or Claude Opus 5 produced about 4 percent of the output tokens the evaluator measured.

• Claude Fable 5.1 set to max reasoning with fallback leads two of Artificial Analysis’ Intelligence Index’s hardest components: AA-Briefcase (1662 Elo, $22.71 and 70.2 minutes per task), which grades multi-week knowledge work projects, each with many tasks and thousands of source files; GDPval-AA v2 (1,764 Elo, $9.77 and 60 turns per task), an adaptation of OpenAI’s test of economically useful tasks across 44 occupations. It also leads SciCode (63.1 percent), which tests models’ ability to write Python for scientific computing problems, and Humanity’s Last Exam (59.1 percent), expert-written questions spanning mathematics, humanities, and natural sciences.

• On the Vals Index, Vals AI’s composite spanning coding, law, medicine, tax, finance, and scientific reasoning, Claude Fable 5.1 set to max reasoning with fallback (68.83 percent, $28.92 and 76 minutes per task) ranks first, ahead of Claude Opus 5 set to max reasoning (67.21 percent, $18.81 and 56 minutes per task) and GPT-6 Astra set to max reasoning (66.61 percent, $19.09 and 25 minutes per task).

Yes, but: Anthropic’s published cybersecurity evaluations all belong to Claude Mythos 5.1 with safeguards off, a configuration most users cannot access. Anthropic says that configuration has the strongest cyber capability of any model it has released and that it sits in the lower of its Frontier Compliance Framework’s two risk tiers but close to the higher tier, reserved for models that can complete novel, autonomous attacks.

Behind the news: Independent benchmarks have presented a moving target this week. Claude Fable 5.1 arrived on September 1. OpenAI’s GPT-6 Astra arrived two days later, initially scoring two points less than Claude Fable 5.1 on Artificial Analysis’ Intelligence Index. Then the scoreboard flickered and resumed with new numbers. On September 4, Artificial Analysis shipped Intelligence Index v4.2, retiring GPQA-Diamond because models had saturated it, adding two harder tests, and doubling the share of the index scored on private tests to 40 percent, which it says reduces labs’ ability to game evaluations. The organization called this an expedited interim update because the frontier was moving too fast to wait for its completed v5 Index. On September 7, Artificial Analysis upgraded their index again, upgrading Terminal-Bench to v4 and adding AutomationBench-AA. After these changes, Claude Fable 5.1 and GPT-6 Astra tied for first.

Why it matters: Anthropic named three issues that Claude Fable 5.1 was built to fix: high cost per task, data retention policies that disappointed enterprise customers, and overly restrictive safeguards. Independent testing supports just one of these unresolved issues to be fixed. Cost per task rose about 20 percent over Claude Fable 5 even after a 75 percent cut to the price of cached input. The 30-day data retention rule still applies to everyone except eligible enterprise customers, who can use zero data retention now and move to Enterprise Frontier Safeguards, which store customer data on their own infrastructure rather than Anthropic’s, later this fall. Only the safeguards are loosened, but not completely. According to Anthropic, developers should expect roughly 60 percent fewer cyber interventions per session in Claude Code.

We’re thinking: A top score on a benchmark has an ever-shrinking shelf life, not only because new models arrive every week, but also because the evaluation that crowns a model this month may not exist by the next month — or even the next week!

Report: Businesses use older AI models to cut costs

Companies are spending less on AI, and it could flash warning signs for the frontier labs.

On Wednesday, Ramp released its monthly AI Index, which tracks AI spend for the payment platform’s users, revealing that adoption and spending are both on the downswing. Though Anthropic widened its lead over OpenAI in the past month, new adoption growth is decelerating, according to the index.

Now, as we’ve reported with previous Ramp data, it’s important to remember the caveat that this only measures Ramp customers, which tend to be tech-focused companies and startups. However, among this group, AI adoption numbers have started to sputter over multiple metrics, according to the report:

• Overall adoption, while still growing, continues to slow down, with the share of US businesses adopting AI hitting 56.1% in August, less than half a percentage point increase month-over-month.

• Per-employee spend on AI also fell nearly 10% the past month, dropping from $7,976 to $7,205 among the top 1% of AI adopting firms. Ara Kharazian, chief economist at Ramp, noted in his letter that there are multiple factors driving down this spend, including the innocuous explanation that many people take off work during the summer months. “We’ve similarly observed declines in AI spend around November and December,” said Kharazian.

• Additionally, AI token spend is declining as the price of AI starts to drop. Ramp’s latest index finds that the “effective price per million tokens” has declined 41% to $0.68 as of the release of the report, down from the 2026 peak of $1.15 in March. For context: OpenAI’s Astra and Anthropic’s Mythos and Fable 5 and 5.1 cost $10 per million input tokens and $50 per million output tokens.

• And as for frontier labs, the usage of their heavyweight models is seemingly lagging. Adoption and spend is largely driven by lower-cost, mid-tier models like Anthropic’s Claude Sonnet or OpenAI’s GPT-5.6 Terra. High-powered frontier models like Opus, Fable, and Sol, meanwhile, drove 45% of token share, down from a 53% peak in August.

“The models driving volume increases are relatively cheap … We’ve heard from

businesses who are imposing company-wide defaults that reduce usage of frontier models,

saying standard models are still highly performant and also more cost effective,” Kharazian wrote.

While the explanation for the decreasing costs could be that companies are leaning into open source models, in reality, the adoption of open source and Chinese alternatives is still limited: According to the report, only 6.4% of businesses that spend on AI use these kinds of models.

What Else Happened in AI from Sept 07th to Sept 13th 2026?

Cognition rolled out SWE-2 inside Devin, a Kimi K3-based coding model that claims to match Fable 5.1 and GPT-6 Astra on certain coding benchmarks while costing 64% less.

Thinking Machines co-founder Andrew Tulloch is moving from Meta to Anthropic, months after initially rejecting Mark Zuckerberg’s reported $1.5B package and then signing on anyway at an undisclosed compensation.

OpenAI denied to the NYT that Tristan Buckmaster’s Codex prompts shaped its Navier-Stokes proof, while claiming “substantial progress” on another Millennium Prize problem.

OpenAI launched ChatGPT for Financial Services, an edition of ChatGPT Work with PitchBook, Crunchbase, and LSEG data baked in for valuation models and pitch decks.

Universal Music Group is partnering with AI audio startup ElevenLabs on a licensing deal, with a fan platform for remixing participating artists’ tracks in development.

Anthropic disclosed a fourth case of Claude breaking into real systems during cyber testing, with METR now conducting an 8-week independent investigation of the incidents.

OpenAI appointed Paul Christiano to the OpenAI Foundation Board and its safety committee, who previously ran OpenAI’s alignment team until 2021 and now advises the U.S. government on testing frontier models.

Instacart rolled out Clementine, an AI grocery assistant that builds a cart from a text message or a photographed shopping list.

Apple is launching Apple Reference Image, a new feature for the iPhone 18 Pro that can determine whether a photo is authentic or AI-generated.

Amazon Prime Video introduced AI lip-syncing on its first show, Maxton Hall, digitally reshaping the actors’ mouths to fit the English dubbing.

An Anthropic “whistleblower” named Jacob Coxon quit the company and shared a viral X post warning about the dangers of rapid AI development. — WIRED

NYU mathematics professor Tristan Buckmaster alleges that OpenAI started working on the Navier-Stokes Millennium Prize problem after learning of his own research, and may have trained its models using his work (along with colleague and Anthropic staffer Levent Alpöge). – TechCrunch

Google will purchase 1 million carbon credits from an Indian startup named Mitti Labs, which pays rice farmers to adopt practices that reduce methane emissions and water use. — TechCrunch

ID verification giant IDScan confirmed a breach exposing more than 150 million driver’s licenses and other government-issued identity documents, including people’s full names. — TechCrunch

OpenAI is ending its $1-a-year pilot program with the US federal government and moving agencies to usage-based pricing at 50% off standard rates. — Bloomberg

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