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. ...

On September 1, 2026, Anthropic released Claude Fable 5.1 and Claude Mythos 5.1. It has been roughly three months since Claude Fable 5 launched, and this time there is no government directive and no surprise shutdown in the story. The headline is different: the sticker price did not move, but the cost of actually running the model dropped sharply. On top of that, Fable 5.1 beats last month’s Claude Opus 5 on every benchmark Anthropic published. Let’s look at the details. ...

Summary: Gemini Omni 1.1 Flash in 30 Seconds Gemini Omni 1.1 Flash is Google’s video generation model, released on 27 August 2026. It replaces Veo 3.1 on the video side. A single generation is still 10 seconds. The headline “40 seconds” is a cumulative length you reach by extending the same video in 10-second steps. When extending, the model now reads up to 10 seconds of prior footage. Previous models only referenced the final second, which is where the consistency gain comes from. You can pin the first and last frame and let the model generate the motion between them. Built for orbit shots, transitions and looping clips. The 360p draft tier runs up to 60% faster at one third of the cost of 720p. Google’s recommended loop: draft at 360p, render the pick at 720p, upscale to 1080p or 4K at the end. 4K is an upscale, not native generation. The model generates 720p; anything above that is an enlargement. Per second: 360p $0.03 · 720p $0.10 · 1080p $0.15 · 4K $0.30. In tokens, $1.50 per million in and $17.50 per million for video out. The API has real gaps: no system instructions, no function calling, no structured output, no context caching. The problem with Google’s video models for the past year was length. An 8-10 second clip is impressive but it isn’t a scene. Gemini Omni 1.1 Flash doesn’t fix that by making the clip longer, it fixes it by making clips stackable. ...

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. ...