Skip to content
BetaAI and tech news.Edition of Sun 1 Nov 2026 
Wire · Latest
AWSManaging Amazon Bedrock costs end to end: A playbook for FinOps and platform teamsAWSPreview web apps live as your coding agent builds them with Amazon Bedrock AgentCore runtimeHugging Facenemotron-halloweenAWSHow Worldwide Express automated freight exceptions with Amazon BedrockAWSConfigure the ChatGPT desktop app with Amazon Bedrock in AWS GovCloud (US)GoogleWe’ve received our first response from the Project Suncatcher prototype satellite.GoogleSee who has access to your Gmail inbox in 2 minutes.NVIDIAThings That Go Beep in the Night: Agentic AI Joins the Search for Extraterrestrial SignalsOpenAIMaking it easier for websites to express AI training preferencesOpenAICommunity safety report and new protections for teensOpenAIFair use benefits everyoneAWSHow the UK Amazon Quick User Group grew in 2026

AI and tech news · Sun 1 Nov 2026

Today1 tool release, 5 papers, 1 outage, 5 rising reposOpen
LeadAIExplainer

What "671 billion parameters" really means: mixture-of-experts explained

Big AI models now quote two sizes, total and active. Here is how mixture-of-experts works and why the gap between the two numbers matters.

By the Machine Notes desk4 min read

Trackers · updated every day

The data desk

Built automatically from free public data: open models, AI research, official rules and code. Every number links to its source.

Notable models, training compute

All models →
10201021102210231024102510261027Q4 '24Q2 '25Q4 '25Q2 '26Q4 '26MAI-Base-2 (Microsoft), Oct 15: 2.4 × 10²⁵ FLOPDeepSeek V4.1 Flash (DeepSeek), Sep 9: 4.3 × 10²⁴ FLOPGPT-6 Astra (OpenAI), Sep 3: 9.4 × 10²⁶ FLOPWeatherNext 3 (Google DeepMind,Google Research), Sep 3: 2.1 × 10²³ FLOPGLM-5.3-Flash (Z.ai (Zhipu AI)), Aug 20: 3.2 × 10²⁴ FLOPMotif-3 (Motif Technologies), Aug 7: 1.1 × 10²⁴ FLOPK-EXAONE 2.0 (LG AI Research), Jul 31: 3.5 × 10²⁴ FLOPA.X K2 (SK Telecom), Jul 29: 1.8 × 10²⁴ FLOPKimi K3 (Moonshot), Jul 16: 2.0 × 10²⁵ FLOPInkling (Thinking Machines), Jul 15: 1.1 × 10²⁵ FLOPLongCat-2.0 (Meituan Inc), Jun 29: 1.0 × 10²⁵ FLOPSolar Open2 250B (Upstage), Jun 28: 1.1 × 10²⁴ FLOPNemotron 3 Ultra (Nvidia), Jun 4: 6.6 × 10²⁴ FLOPComposer 2.5 (Cursor), May 18: 3.9 × 10²⁵ FLOPDeepSeek-V4-Flash (DeepSeek), Apr 24: 2.5 × 10²⁴ FLOPDeepSeek-V4-Pro (DeepSeek), Apr 24: 9.7 × 10²⁴ FLOPMiMo-V2.5-Pro (Xiaomi Corp), Apr 23: 6.8 × 10²⁴ FLOPEXAONE 4.5 (LG AI Research), Apr 9: 3.9 × 10²⁴ FLOPMolmoAct 2 (Allen Institute for AI,University of Washington,National University of Singapore,University of Pennsylvania,Johns Hopkins University,Amazon,Cortex AI), Apr 5: 1.1 × 10²² FLOPComposer 2 (Cursor), Mar 19: 2.3 × 10²⁵ FLOPGLM-5 (Z.ai (Zhipu AI)), Feb 12: 6.8 × 10²⁴ FLOPKimi K2.5 (Moonshot), Feb 2: 5.8 × 10²⁴ FLOPK-EXAONE (LG AI Research), Dec 31, 2025: 1.5 × 10²⁴ FLOPSolar Open 100B (Upstage), Dec 31, 2025: 1.4 × 10²⁴ FLOPGLM-4.7 (Z.ai (Zhipu AI)), Dec 22, 2025: 4.4 × 10²⁴ FLOPNemotron 3-Nano-30B-A3B (Nvidia), Dec 15, 2025: 4.8 × 10²³ FLOPOlmo 3 (Allen Institute for AI), Nov 20, 2025: 1.1 × 10²⁴ FLOPKimi K2 Thinking (Moonshot), Nov 6, 2025: 4.2 × 10²⁴ FLOPLing-1T (Ant Group), Oct 10, 2025: 6.0 × 10²⁴ FLOPGLM-4.6 (Z.ai (Zhipu AI),Tsinghua University), Sep 30, 2025: 4.4 × 10²⁴ FLOPQwen3-VL-235B-A22B (Alibaba), Sep 23, 2025: 5.0 × 10²⁴ FLOPQwen3-Omni-30B-A3B (Alibaba), Sep 22, 2025: 3.6 × 10²² FLOPAgentFounder-30B (Alibaba), Sep 16, 2025: 6.5 × 10²³ FLOPQwen3-Max (Alibaba), Sep 5, 2025: 1.5 × 10²⁵ FLOPLongCat-Flash (Meituan Inc), Sep 1, 2025: 3.7 × 10²⁴ FLOPGPT-5 (OpenAI), Aug 7, 2025: 6.6 × 10²⁵ FLOPgpt-oss-120b (OpenAI), Aug 5, 2025: 4.9 × 10²⁴ FLOPgpt-oss-20b (OpenAI), Aug 5, 2025: 5.5 × 10²³ FLOPGLM-4.5 (Z.ai (Zhipu AI),Tsinghua University), Jul 28, 2025: 4.4 × 10²⁴ FLOPQwen3-235B-A22B (Jul 2025) (Alibaba), Jul 25, 2025: 4.8 × 10²⁴ FLOPQwen3-235B-A22B-Thinking (Jul 2025) (Alibaba), Jul 25, 2025: 4.8 × 10²⁴ FLOPQwen3-Coder-480B-A35B (Alibaba), Jul 22, 2025: 1.6 × 10²⁴ FLOPEXAONE 4.0 (32B) (LG AI Research), Jul 15, 2025: 2.7 × 10²⁴ FLOPKimi K2 (Moonshot), Jul 11, 2025: 3.0 × 10²⁴ FLOPGrok 4 (xAI), Jul 9, 2025: 5.0 × 10²⁶ FLOPFGN (Google DeepMind), Jun 12, 2025: 9.6 × 10²¹ FLOPDeepSeek-R1 (May 2025) (DeepSeek), May 28, 2025: 4.0 × 10²⁴ FLOPSeed1.5-VL (ByteDance), May 11, 2025: 1.4 × 10²⁴ FLOPQwen3-235B-A22B (Alibaba), Apr 29, 2025: 4.8 × 10²⁴ FLOPPangu Ultra (Huawei), Apr 10, 2025: 1.1 × 10²⁵ FLOPLlama 4 Behemoth (preview) (Meta AI), Apr 5, 2025: 5.2 × 10²⁵ FLOPLlama 4 Maverick (Meta AI), Apr 5, 2025: 2.2 × 10²⁴ FLOPLlama 4 Scout (Meta AI), Apr 5, 2025: 4.1 × 10²⁴ FLOPDeepSeek-V3 (Mar 2025) (DeepSeek), Mar 24, 2025: 3.3 × 10²⁴ FLOPEXAONE Deep 32B (LG AI Research), Mar 16, 2025: 1.3 × 10²⁴ FLOPHunyuan-TurboS (Tencent), Mar 11, 2025: 5.4 × 10²⁴ FLOPQwQ-32B (Alibaba), Mar 6, 2025: 3.5 × 10²⁴ FLOPGPT-4.5 (OpenAI), Feb 27, 2025: 3.8 × 10²⁶ FLOPClaude 3.7 Sonnet (Anthropic), Feb 24, 2025: 3.4 × 10²⁵ FLOPGrok 3 (xAI), Feb 17, 2025: 3.5 × 10²⁶ FLOPDeepSeek-R1 (DeepSeek), Jan 20, 2025: 3.5 × 10²⁴ FLOPEagle 2 (Nvidia,Nanjing University,Tsinghua University,Hong Kong Polytechnic University,Johns Hopkins University,New York University (NYU)), Jan 20, 2025: 4.7 × 10²² FLOPEurus-2-7B-PRIME (Tsinghua University,University of Illinois Urbana-Champaign (UIUC),Shanghai AI Lab,Peking University,Shanghai Jiao Tong University,CUHK Shenzhen Research Institute), Jan 2, 2025: 4.0 × 10²⁰ FLOPDeepSeek-V3 (DeepSeek), Dec 24, 2024: 3.3 × 10²⁴ FLOPEXAONE 3.5 32B (LG AI Research), Dec 9, 2024: 1.3 × 10²⁴ FLOPLlama 3.3 70B (Meta AI), Dec 6, 2024: 6.9 × 10²⁴ FLOPAmazon Nova Pro (Amazon), Dec 3, 2024: 6.0 × 10²⁴ FLOPHunyuan-Large (Tencent), Nov 6, 2024: 3.5 × 10²⁴ FLOPGPT-6 ASTRAGROK 4GPT-4.5Training compute, FLOP (log scale)
Each dot is one model, last 24 monthsData: Epoch AI, CC BY 4.0

Explainers

The basics
01AI · Explainer

What "671 billion parameters" really means: mixture-of-experts explained

Big AI models now quote two sizes, total and active. Here is how mixture-of-experts works and why the gap between the two numbers matters.

Read · 4 min
02AI · Explainer

How to read an AI benchmark: ECI, Arena and the numbers in launch posts

Launch posts quote test scores, arena ranks and composite indexes. Here is what each one measures, how it goes wrong and what to ask.

Read · 4 min
03AI · Analysis

Best AI for coding in 2026: what the benchmarks show and what they miss

The top coding models are within a few points of each other, and the scores come mostly from the companies selling them. Here is how to read them.

Read · 4 min
04Money · Explainer

Who is paying for the AI data-centre boom? Bonds, private credit and off-books deals explained

Big Tech pays for AI data centres in five main ways, from its own cash to joint ventures that keep the debt off its books. Here is how each one works.

Read · 4 min
05AI · Explainer

Can an AI model hide what it can do? What the research actually shows

Lab studies show models can underperform on purpose, fake compliance and carry hidden triggers. Here is what was shown, and what it does not prove.

Read · 5 min
06AI · Explainer

What are tokens, and why does every AI company charge by them?

AI models read and write in small chunks of text called tokens. Here is how they work, and how to use them to estimate what a task will cost.

Read · 5 min
07AI · Explainer

What is an open-weight model, and is it really open source?

Many AI labs now let you download their models. What you get, what the licence allows and why "open" rarely means open source.

Read · 4 min
08AI · Explainer

AI agent, chatbot or assistant? The difference in one table

Three words for software you talk to. The real difference is who picks the next step, and what the software is allowed to touch.

Read · 4 min
09AI · Explainer

What is generative AI? How one idea writes text, draws images and codes

Generative AI makes new text, images, code, audio and video by learning the patterns in huge amounts of data. Here is how it works and where it fails.

Read · 4 min
10AI · Explainer

What is an AI agent?

A language model that can take steps on its own, check what happened and try again. Here is what that means and where it breaks.

Read · 6 min
11Money · Explainer

What is capex, and why AI needs so much of it

Capital expenditure is money spent on things that last. For Big Tech right now, that mostly means data centres full of AI chips.

Read · 6 min
12Chips · Explainer

Why GPUs cost so much

The chips that train AI models are scarce, hard to make and wrapped in software nobody else has. Here is where the price comes from.

Read · 5 min