Ai News

GPT-6 Astra in 30 Seconds GPT-6 Astra is OpenAI’s new flagship, announced on September 3, 2026. The company calls it “the world’s most intelligent and aligned model”. There is no Sol/Terra/Luna split this time. The lineup is Astra and Astra Pro. API pricing is $10 per million input tokens and $50 per million output tokens: 2.5x GPT-5.6 Sol’s promotional price, and identical to Claude Fable 5.1. The scores are high but footnoted. The headline 98.6% on ARC-AGI-3 came from a custom harness; the same model scores 62.7% on the standard one. Astra is the first OpenAI model to cross the Critical cybersecurity threshold in the Preparedness Framework. Standard access refuses parts of that work outright. Rollout is staged: Daybreak enterprise customers first, then Plus, Pro, Business, Enterprise, the API and AWS. Pro, Business and Enterprise also get Astra Pro. OpenAI launched GPT-6 Astra today, September 3, 2026. At the press briefing, president Greg Brockman first conceded that AGI remains a “gray, fuzzy thing”, then went ahead anyway: “I think it’s not unreasonable to feel that we are now in the AGI era.” He closed with the same line: “Welcome to the AGI era.” ...

TL;DR: Gemini 3.8 Flash in 30 seconds Gemini 3.8 Flash landed on September 2, 2026, three weeks after 3.7 Flash. That is the third Flash release in three months. Price did not move: $0.75 input, $3.75 output per million tokens. The promo ends December 31, 2026, then it doubles. A second model shipped alongside it: Gemini 3.8 Flash Cyber, tuned for vulnerability discovery and locked behind the new Fairwind Program. The benchmark table is split. It tops the chart on finance, legal, long video and chart reasoning, and it trails Claude Opus 5 badly on long horizon terminal and computer use work. The model “works harder”: more reasoning steps, more iterative tool calls. Same sticker price, potentially a bigger bill. The Flash release cadence has stopped being funny. 3.6 Flash shipped on July 21, 3.7 Flash on August 13, and Gemini 3.8 Flash today, September 2, 2026. Three releases in three months. ...

Summary: GLM-5.3-Flash in 30 Seconds GLM-5.3-Flash is Z.ai’s (formerly Zhipu AI) new model, released 26 August 2026. It is the first natively multimodal member of the GLM-5 series: text and images go through the same model. It is 320 billion parameters, but only 18 billion run per token. Layer count is roughly half of GLM-4.5’s: 45 against 92. The licence is MIT. Most strong Chinese models this summer shipped under bespoke community licences; here there is no fine print to read before shipping a product. It beats GLM-5.2 by a wide margin on coding and agentic tests (63.4 against 46.2 on DeepSWE) and approaches Claude Opus 4.8 overall, at roughly one tenth of GLM-5.2’s price. API pricing is $0.15 in / $0.50 out per million tokens, or $0.075 and $0.25 with the 50% discount running until 9 September 2026. It is the first model in the series to use hybrid attention: linear attention carries local dependencies, sparse attention retrieves distant context. Against GLM-5.3 that is 3x less attention compute and a 4.4x smaller KV cache. Before launch it was tested anonymously as ox-alpha on OpenCode and OpenRouter, where it became the most used model of the week. All of that traffic was served on Chinese AI chips. There is one race in open-weight models this summer: producing the same intelligence with less compute. Alibaba’s Qwen3.8-Flash-Next beat its own 397B sibling with 6 billion active parameters. Z.ai’s answer is GLM-5.3-Flash: 320 billion total parameters with only 18 billion running per token, leaving GLM-5.2 behind at a tenth of the cost. ...

Summary: Qwen3.8-Flash-Next in 30 Seconds Qwen3.8-Flash-Next is Alibaba’s new AI model, out in August 2026. It reads text and images and writes text back, tuned for writing code and running multi-step work on your behalf. Anyone can download the model files, live since 24 August. The license is not fully permissive though, so read it before shipping it in a product. The real story: Alibaba shipped this as a dry run for the next big release, Qwen4. The identifier inside the model files literally says qwen4_exp, as in “Qwen4 experimental”. It is 125B parameters in size, but only 6B of them run for any given word. Big-model knowledge, small-model bill. It reads about 750,000 words in one go (1M tokens), and at that length it is 8x faster than its much larger sibling. Training it cost roughly 1/9 of the 397B Qwen3.7-Plus, and it still beats that model on coding and office work. It is cheap to run: $0.16 in / $0.47 out per million tokens. The flagship in the same family costs 12x that. When Alibaba shipped Qwen3-Next, the pitch was: this is not a finished product, it is next generation’s architecture released early so the community can poke at it. That architecture then carried the whole Qwen3.5 through Qwen3.8 line. ...

Summary: Gemini 3.7 Flash in 30 Seconds Gemini 3.7 Flash landed on August 13, 2026, only three weeks after 3.6 Flash. Introductory pricing is $0.75 in / $3.75 out per 1M tokens: half of 3.6 Flash’s standard rate. The promo ends December 31, 2026. Coding jumped hard: FrontierCode 1.1 went from 34.4% to 43.6%, DeepSWE v1.1 from 48.6% to 65.3%. Context window is 1,048,576 tokens with a 65,536 token output cap. It takes text, images, video, audio and PDF. It is not the smartest model on the board: 56 on the Artificial Analysis index, one point behind GPT-5.6 Terra and Muse Spark 1.2, at roughly a third of their price. Google’s Flash line has never been about winning the intelligence crown. It is the model you run at volume: cheap enough to call thousands of times a day, fast enough to sit inside a product. Gemini 3.7 Flash stretches that definition. ...