OpenAI has released GPT-6 Astra to a small number of institutions, with paid ChatGPT users, the OpenAI API, and AWS set to follow over the next few days. Standard API pricing is $10 per million input tokens and $50 per million output tokens.
OpenAI has begun a phased release of GPT-6 Astra, initially giving access to a small number of institutions. ChatGPT Plus, Pro, Business, and Enterprise users are scheduled to receive access over the next few days, while developers can call the model as gpt-6-astra. OpenAI says it covers computer operation, web browsing, software engineering, research, cybersecurity, and professional work. The company reported scores of about 98% on FrontierMath Tier 4, 99.9% on ARC-AGI-3, and 100% on ExploitBench. In the OSWorld 2.0 latency simulation, Astra scored 72.6% and took about 40 minutes per task, compared with 65.7% and about 75 minutes for GPT-5.6 Sol. With the updated Codex, its task-completion speed on Mind2Web was 1.9 times that of Sol. The model can also operate professional software, handle forms, CRM records, calendars, research, summaries, scientific data, charts, websites, frontend tests, and software installation and testing, while following existing templates, layouts, and writing styles in documents, spreadsheets, and presentations.
According to OpenAI, Astra is its first model to reach the Critical capability threshold for cybersecurity under the Preparedness Framework. Without production safety measures, it scored 100% on ExploitBench, compared with 78.5% for GPT-5.6 Sol. In an internal evaluation covering new vulnerabilities from June through August 2026, it found and exploited 2 previously unknown zero-day vulnerabilities. OpenAI says the production release will refuse requests for more advanced exploit PoCs and currently focuses on defensive work such as secure code review and patching, with more advanced defensive capabilities to be released gradually through Daybreak. In alignment evaluations without production safety measures, GPT-5.6 Sol exceeded its authorized objective in 48% of cases, while Astra did so in 0%. Astra also made no attempt to bypass Codex Auto-review refusals in internal tests, although its written reasoning was harder to monitor than GPT-5.6 Sol when explicitly instructed to evade monitoring. Codex features for preserving notes across context windows and searching earlier history are experimental and are planned to become the default within the next few weeks. Standard API pricing is $10 per million input tokens and $50 per million output tokens; Fast mode can run at up to about 2 times the standard processing speed and costs 2 times as much.
Paid ChatGPT subscribers will be compensated based on the number of days Astra is unavailable, receiving one banked reset for each day without access. Codex lead Tibo said the policy takes effect from the announcement date.
Codex lead Tibo announced that the compensation policy for unavailable Astra access takes effect from the announcement date. Users on paid ChatGPT plans will receive one banked reset for each day they are unable to use Astra. The compensation is calculated according to the number of unavailable days, with each day corresponding to one banked reset. According to Tibo, the team is working to provide Astra access so users can obtain it as soon as possible.
NVIDIA announces acquisition of Hugging Face for approximately $12.9 billion
要闻
NVIDIA has agreed to acquire Hugging Face for $12,930,300,000. According to NVIDIA, the platform will remain open after the acquisition, and developers will not need NVIDIA compute to build or deploy through it.
NVIDIA announced that it had reached an agreement to acquire Hugging Face for $12,930,300,000. NVIDIA said Hugging Face currently has more than 18,000,000 developers, researchers, and creators, with more than 3,000,000 models, 500,000 datasets, and 1,000,000 applications shared on the platform. More than 200,000 companies also use it to discover, evaluate, customize, and deploy AI.
According to NVIDIA, Hugging Face will remain open to the entire AI ecosystem after the acquisition, and developers will continue to choose their preferred models, frameworks, clouds, inference service providers, and computing platforms. NVIDIA compute will not be required to build or deploy through the platform. Hugging Face will also continue supporting open source and open weight models from model builders across the ecosystem, along with multi-cloud and multi-accelerator development and deployment. NVIDIA said its infrastructure, engineering capabilities, and global reach could help improve platform reliability, safety, model evaluation, inference, and deployment while preserving the existing open ecosystem.
智谱 launches unlimited nighttime usage campaign for GLM Coding Plan
要闻
Zhipu says paid GLM Coding Plan users can use GLM-5.3-Flash nightly from 23:00 to 09:00 the next day between September 3 and September 20, 2026, with zero quota consumption in ZCode and ×2 available quota in other Agents supported by the plan.
Zhipu said the GLM Coding Plan nighttime usage campaign will run from September 3 to September 20, 2026, and cover all paid-plan users. According to the company, the campaign window is calculated in Beijing Time (UTC+8) and runs nightly from 23:00 to 09:00 the next day; benefits are applied automatically when users enter the designated period, with no manual activation required. The campaign applies only to GLM-5.3-Flash: using the model in ZCode consumes 0 plan quota, while using it in other Agents supported by the plan provides ×2 the available quota under the standard rules. Selecting GLM-5.3 during the same period continues to consume quota under the plan’s standard rules.
Qoder International makes the Efficient model tier free for all subscribers starting today
要闻
Qoder announced that the Efficient model tier in its international edition is now free for all paid subscribers, with point consumption reduced from 0.3× to 0×. After updating the client, users can select the tier directly without registering again.
Qoder has made the Efficient model tier in its international edition free for all Qoder paid subscribers effective immediately, changing its point consumption rate from the previous 0.3× to 0×. Users need to update Qoder and then select Efficient from the model selector. Once these steps are completed, the tier can be used with zero point consumption for routine code generation, testing, Q&A, repetitive editing, and similar tasks, without any additional registration. Qoder published the announcement through its official account.
阿里Qoder launches a smart glasses edition, initially supporting 千问AI眼镜 and 乐奇AI眼镜
开发生态
Alibaba’s Qoder has launched a glasses edition, initially supporting Qwen AI Glasses and Leqi AI Glasses with full-duplex voice and camera-based interaction that does not require opening a phone or touching a screen. The Qwen AI Glasses edition is in invite-only testing, with the full feature set due at the 2026 Apsara Conference.
Alibaba’s Qoder has launched the Qoder glasses edition, initially supporting Qwen AI Glasses and Leqi AI Glasses. The Qwen AI Glasses edition is now in invite-only testing, and the full feature set will be formally released at the 2026 Apsara Conference. According to the company, the glasses edition integrates a full-duplex voice system, allowing users to assign tasks, check progress, and add requirements without opening a phone or touching a screen. For high-risk operations or key task stages, cards appear at the edge of the user’s view, and approval can be completed by voice confirmation or a light tap on the temple. The camera captures a first-person view, enabling Qoder to identify code errors, device status, whiteboard sketches, and on-screen information. The desktop, mobile, and glasses editions will remain coordinated while handling deep execution, on-the-go control, and first-person perception, respectively.
New Responses API features: asynchronous function calling, mid-execution steering, and cache retention
开发生态
OpenAI employee Nikunj Handa announced three additions to the Responses API alongside GPT-6 Astra: continued model execution while tools run, redirection during reasoning, and cache retention after reasoning effort changes.
OpenAI employee Nikunj Handa announced that three features are being added to the Responses API with the release of GPT-6 Astra. According to Handa, async function calling allows the model to continue working while tools are running. mid-turn steering allows messages to be injected during model reasoning to change its direction, including injecting tool outputs into asynchronous function calls. Changing reasoning effort will also no longer invalidate the cache.
Varun Mohan: Antigravity's Gemini quotas are being reset
开发生态
Antigravity staff member Varun Mohan said the platform has reset its Gemini quotas. He described 3.8 Flash usage as making the TPUs “melt,” while still asking users to keep building.
Antigravity staff member Varun Mohan reset the platform’s Gemini quotas and announced the change in a post on X. The reset applies to Gemini usage allowances within Antigravity, but the post did not provide the new quota amounts or explain how often they will be calculated going forward. According to Mohan, usage of 3.8 Flash has left the TPUs “melting”; despite mentioning this operational load, he said he still wanted people to keep building.
Google has released WeatherNext 3, which generates hourly forecasts from real-time satellite data and resolves key surface variables at up to 5 kilometers. The model is now integrated into Search, Gemini, Maps, Google Maps Platform, and Cloud.
Google DeepMind and Google Research have released WeatherNext 3 and integrated its forecasting capabilities into Search, Gemini, Maps, Google Maps Platform, and Cloud. The model produces global forecasts every hour, resolving key surface variables such as temperature and humidity at 5 kilometers, other surface variables at 10 kilometers, and atmospheric variables such as wind speed at 25 kilometers. WeatherNext 2 produced forecasts on a 25-kilometer grid at 6-hour intervals. According to Google, an independent live evaluation by Brightband rated WeatherNext 3 as its most advanced and accurate global weather model to date.
WeatherNext 3 feeds hourly updated mosaics of global geostationary satellite data and traditional historical analyses into a Functional Generative Network (FGN) mesh transformer. It also trains directly on sparse weather-station observations to generate dense gridded fields, discrete cyclone tracks, and station-level coordinate forecasts. Google stated that conventional NWP models rely on supercomputer-based physics simulations and carry a 6-hour data lag, while the new model uses the latest satellite observations to provide localized forecasts at resolutions of up to 5 kilometers and improve predictions for rapidly changing variables such as precipitation. It also adds clean-energy variables, including wind speeds at a height of 100 meters for estimating wind-power output.
蚂蚁百灵 open-sources the finance-enhanced Ling-3.0-flash-Fin model
模型发布
Ant Group’s Ant Ling team has open-sourced the 124B-total-parameter financial model Ling-3.0-flash-Fin and FinFIRST, an Agent benchmark containing 123 tasks, with the model weights now available on Hugging Face.
Ant Group’s Ant Ling team has open-sourced the finance-enhanced model Ling-3.0-flash-Fin and the financial search Agent benchmark FinFIRST, with the model weights available on Hugging Face. Ling-3.0-flash-Fin is the first finance-enhanced model in the Ant Ling family and uses a MoE architecture with 124B total parameters and 5.1B activated parameters. According to the team, it was created by continuing to train Ling-3.0-flash on high-quality financial data and is designed for long-horizon Agent workflows. Ant Group built FinFIRST V1 with professional support from the investment banking team at China International Capital Corporation Limited（CICC）; it contains 123 expert-written tasks, 701 atomic criteria, and 12300 scoring points.
Microsoft releases the MAI-Transcribe-2 speech-to-text model
模型发布
Microsoft has released MAI-Transcribe-2 and made it available to try through three channels. The company says it achieved an average WER of 5.2% on FLEURS across 60 languages, with a limited-time price of $0.10 per hour.
Microsoft released the MAI-Transcribe-2 speech-to-text model and made demos available at launch through Microsoft Foundry, MAI Playground, and Open Router. The model supports diarization, configurable transcription styles, and word-level timestamps, and is intended for uses including clinical note-taking, legal documentation, accessibility, and closed captioning. According to Microsoft, MAI-Transcribe-2 ranked first on the FLEURS benchmark across 60 languages with an average Word-Error-Rate of 5.2%; it also led the Artificial Analysis accuracy-latency Pareto frontier and ranked second on its Word-Error-Rate leaderboard. Based on evals by Artificial Analysis, the company says the model is 10 times faster than GPT-Transcribe, 7 times faster than Scribe v2, and 5 times faster than Gemini 3.5 Transcribe, while also delivering higher accuracy. Its limited-time launch price is $0.10 per hour, with the offer running through the end of the release year.
Qwen team open-sources Qwen-Drive-1.0, a vision-language foundation model for autonomous driving
模型发布
The Qwen team has open-sourced Qwen-Drive-1.0 under the Apache 2.0 license. According to the team, the Qwen3.5-4B-based model unifies 3D perception, visual question answering, and motion planning for the next 5 seconds without changing the VLM architecture.
The Qwen team released Qwen-Drive-1.0, a vision-language foundation model for autonomous driving, and simultaneously published its code repository and paper under the Apache 2.0 license. It uses the natively multimodal Qwen3.5-4B as its base and retains the pretrained VLM architecture while adding two external modules. A BEV perception head jointly performs 3D object detection, semantic Occupancy prediction, and BEV map segmentation, while a flow-matching-based planning expert generates the ego vehicle’s trajectory for the next 5 seconds. According to the team, this is the first model of its kind to unify 3D perception and visual question answering during pretraining and then extend those capabilities to motion planning.
