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Claude, the research, and Anthropic's product moves — the lab whose models power much of what builders ship, this site included.
Moonshot AI released Kimi K3, the largest open-weight model yet: a 2.8-trillion-parameter mixture-of-experts (16 of 896 experts active), 1M-token context, native vision, Kimi Delta Attention and Attention Residuals, in K3 Max and K3 Swarm variants. Moonshot's own benchmarks show K3 beating Anthropic's Opus 4.8, while independent Artificial Analysis scores it clearing Opus 4.8 and GPT-5.5 but losing to Fable 5 and GPT-5.6 Sol; it lists at $3/$15 per million tokens, roughly half Opus's cost per task. Ask it who it is and it says "I am Claude" — the tell of the distillation Anthropic documented in February (3.4M exchanges from Moonshot, 16M across three Chinese labs via 24,000 fake accounts). Also: Mira Murati's Thinking Machines ships its first model, the 975B open-weight Inkling; an autonomous AI agent breaches Hugging Face and is caught with the open-weight GLM 5.2; and NotebookLM becomes Gemini Notebook with a sandboxed cloud computer in every notebook.
Anti-AI-slop design skill for Claude Code, Cursor, and Codex.
This is today’s edition of The Download , our weekday newsletter that provides a daily dose of what’s going on in the world of technology. There’s a lot of hype around perimenopause. Don’t buy it. Perimenopause used to be considered taboo, but not anymore. Thanks at least in part to TV doctors and social media influencers, conversations about the sometimes years-long period before menopause are now more open than ever. But the conversation is increasingly shaped by misinformation. Despite what some marketers will claim, there is no test for perimenopause. That doesn’t mean women should have to put up with symptoms, but treatment suggestions often lack scientific evidence. And not all the symptoms women experience in midlife can be blamed on hormones. Read the full story on the hype and misinformation surrounding perimenopause . —Jessica Hamzelou This article is from The Spark, our weekly climate tech newsletter. Sign up to receive it in your inbox every Wednesday. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 China’s AI gap with the US may have just narrowed A Chinese startup has released the world’s largest open AI model. ( Reuters $) + It competes with some Anthropic and OpenAI models. ( Gizmodo ) + The model’s launch sent AI and semiconductor stocks sliding. ( Bloomberg $) + Chinese Nvidia alternatives are also gaining traction. ( SCMP ) + Xi Jinping pitched China as an AI partner to the developing world. ( CNBC ) + The country is betting big on open-source. ( MIT Technology Review ) 2 Trump Media is selling instant access to “market-moving’ social posts It’s developed a new way to monetize the president’s posts. ( Quartz ) + And Trump could profit directly from selling access to his statements. ( BBC ) + Kalshi says it caught Trump’s teleprompter operator insider trading . ( Verge ) 3 Astronomers have found an atmosphere on a nearby Earth-like planet It’s the first potent
196 points, 300 comments on HN
South Korea is developing its own security-focused AI model and hopes to bring it online by the end of the year, to ensure the nation has sovereign bug-finding capabilities. Deputy Prime Minister and Minister of Science and ICT Bae Kyung-hoon revealed the effort to create the model yesterday, and said it’s needed so South Korea possesses a bug-finding model to rival Anthropic’s Mythos. The US government has twice blocked access to Mythos, once by requiring Anthropic to offer it only to American citizens – a demand the AI company could not meet and therefore blocked all access – and a second time by ordering the company to take down its services so Washington could investigate allegations of possible dangerous performance problems. Those incidents led many other nations conclude that the US could in future deny access to powerful models – meaning US-based organizations and national security agencies would have an edge. Washington has since allowed limited access to Mythos to some of its allies. Interest in developing sovereign AI capacity has nonetheless soared, and Bae said South Korea now aspires to develop its own Mythos-class model. The Register is aware of another effort to create Mythos-like tools, involving private firms and infrastructure operators across several countries. In South Korea, the government’s approach is to add security-related information to the corpus it is using to train a locally developed frontier model. The minister said he expects that security-capable model will debut by the end of 2026. South Korea has also sought bids to create a chatbot that will be made freely available to all residents, plus an agentic application that will help locals interact with government services. Minister Bae made his remarks at a policy briefing session conducted by President Lee Jae Myung, during which discussions about AI also touched on using the technology to detect fake news in real time, and put it to work handling complaints about government services
Z.ai GLM has been getting a bit too much love recently , so it’s time for Kimi K3 to fight back! It’s hard to put the scale of today’s open model release in perspective, so thankfully Moonshot AI did it for us : Their vibe reel was entirely edited by Kimi K3 and worth a watch: You can read SimonW and Arena for standard takes and rankings, none of which will be particularly unexpected given the large size of the model, but this pic best summarizes the K2.5 to K3 jump: AI News for 7/15/2026-7/16/2026. We checked 12 subreddits, 544 Twitters and no further Discords. AINews’ website lets you search all past issues. As a reminder, AINews is now a section of Latent Space . You can opt in/out of email frequencies! AI Twitter Recap Moonshot AI launched Kimi K3 as a frontier-class open-weights model, with official claims that place it near top closed models and above prior open competitors. Moonshot officially introduced Kimi K3 as “Open Frontier Intelligence” with 2.8T total parameters , 1M-token context , native multimodal input , Kimi Delta Attention (KDA) , and Attention Residuals , and said the model is live on Kimi.com, Kimi Work, Kimi Code, and API, with open weights promised by July 27, 2026 @Kimi_Moonshot Moonshot also highlighted product positioning around long-horizon agentic coding and self-evolving workflows , plus “vision in the loop” coding/game-building workflows that iterate between code and screenshots @Kimi_Moonshot Before the formal announcement, multiple accounts circulated leaked or app-sourced details that K3 was 2.8T params , calling it the largest open-weight model ever if weights ship as promised @scaling01 , @scaling01 , @eliebakouch The official Kimi blog went live later and was widely shared as the primary technical source @Jianlin_S , @scaling01 , @Yulun_Du Moonshot’s own phrasing acknowledged a limitation: despite being highly competitive overall, K3 still has a “noticeable gap in user experience” versus Claude Fable 5 and GPT-5.6 Sol @scaling01
<p><strong><a href="https://developer.puter.com/labs/firefox-wasm/">Firefox in WebAssembly</a></strong></p> This is absurdly cool: Puter compiled Firefox to WebAssembly such that the whole browser runs in another browser.</p> <p>Here's my blog, running in Firefox, running in WebAssembly, running in Chrome:</p> <p><img alt="A Chrome window. The tab has the Firefox UI and has loaded my blog. On the right is the Chrome network panel showing that it loaded resources that include a 233MB gecko.wasm and an 18MB chrome-assets.tar.zst" src="https://static.simonwillison.net/static/2026/firefox-wasm.webp" /></p> <p>They chose Firefox/Gecko because it has strong single-process support. The project used an estimated $25,000 worth of Claude Opus and Fable tokens, but took advantage of a Claude Max subscription plan so cost much less in actual dollars.</p> <p>The demo funnels all traffic over a WebSocket protocol (using the <a href="https://github.com/MercuryWorkshop/wisp-protocol">Wisp protocol</a>) through Puter's server - a requirement to get this kind of thing to work because code running in browsers can't open arbitrary network connections.</p> <p>(That proxying sounds expensive! The team <a href="https://news.ycombinator.com/item?id=48926939#48936563">had to scale the servers up</a> to handle the traffic during the Hacker News conversation about the project.)</p> <p>Puter claim this supports end-to-end encryption and that looks to be true - I inspected the WebSocket messages and traffic to my own HTTPS site was encrypted whereas requests and responses to <code>http://www.example.com/</code> were in cleartext.</p> <p><a href="https://github.com/HeyPuter/firefox-wasm">Here's the repo</a> for <code>firefox-wasm</code>. <a href="https://github.com/theogbob/WebkitWasm">theogbob/WebkitWasm</a> is a similar project that compiles WebKit to WASM, but that one doesn't currently have an accessible online demo. <p><small></small>Via <a href="https://news.ycombinator.com/item?id=4892693
<p>Chinese AI lab Moonshot AI <a href="https://www.kimi.com/blog/kimi-k3">announced Kimi K3</a> this morning, describing it as their "most capable model to date, with 2.8 trillion parameters". It's currently available via their website and API, but an open weight release is promised "by July 27, 2026".</p> <p>Moonshot are calling this the first "open 3T-class model" (I guess they're rounding 2.8 trillion up to 3 trillion), taking the crown from <a href="https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro">DeepSeek's 1.6T v4 Pro</a>. Their <a href="https://www.kimi.com/blog/kimi-k3#full-benchmark-table">self-reported benchmarks</a> have K3 mostly beating Claude Opus 4.8 max and GPT-5.5 high, while losing out to Claude Fable 5 and GPT-5.6 Sol.</p> <p>A few highlights from the <a href="https://twitter.com/ArtificialAnlys/status/2077832874183860404">Artificial Analysis report</a> on the model:</p> <ul> <li>"On our private long-horizon knowledge work evaluation, Kimi K3 reaches an overall Elo of 1547, +732 points from Kimi K2.6 and behind only Claude Fable 5."</li> <li>"Cost per task ($0.94) is similar to GPT-5.6 Sol ($1.04), ~1/2 the price of Opus 4.8 ($1.80) and higher than open weights peers"</li> <li>"Kimi K3’s token usage on the Artificial Analysis Intelligence Index decreased significantly, using 21% fewer output tokens than K2.6."</li> </ul> <p>The model is also now the <a href="https://twitter.com/arena/status/2077824029126504525">leading model on Arena.ai's Frontend Code arena</a>, surpassing even Claude Fable 5.</p> <p>The new model is notable for the pricing: $3/million input tokens and $15/million output tokens, putting it at the same level as Anthropic's Claude Sonnet series and making it the most expensive model released by a Chinese AI lab to date. This is a significant increase on their earlier models <a href="https://platform.kimi.ai/docs/pricing/chat-k26">such as Kimi K2.6</a> at $0.95/$4. 2.8 trillion parameters is also more than twice the size of that
Forrester warns that customers should brace for bigger software bills next year as software and AI vendors raise prices and pile on usage charges. Working from a survey of more than 2,600 business and technology decision-makers, the tech research company said software budgets were expected to rise "as vendors increase prices or add usage charges to pass their AI costs to customers." In the last six months, Anthropic, OpenAI, and GitHub have shifted some services away from flat-rate subscriptions toward usage-based billing, prompting cost concerns among users. Forrester added Microsoft to the list, citing its recent launch of the premium E7 license, which bolts M365 Copilot, Agent 365, and security tools onto E5. Last year, consultants Bain & Company estimated that the build cost for AI datacenters would hit $2 trillion by 2030. Forrester said that AI would drive increases in data and software spending, with 80 percent of decision-makers expecting those budgets to rise. Sharyn Leaver, chief research officer at Forrester, said: "The organizations that outperform in 2027 won't be those that spend the most on AI. They'll be the ones that invest in the foundations that make AI effective: trusted data, strong governance, organizational readiness, and the ability to continuously adapt as technology and customer behavior evolve." Forrester also found that personnel costs have yet to fall, despite the "AI washing of layoffs" in the tech industry. "While several tech giants, including Oracle, Microsoft, and Meta, have announced significant layoffs in recent months, IT staffing spend has not declined in recent years," the report said. Staffing accounted for 35 percent of IT budgets in 2025. For 2027, 67 percent of tech decision-makers expected to increase their staffing budget, while 23 percent said it would stay flat, and 10 percent expected it to decline. "The AI washing of layoffs will continue as vendors trim for financial and restructuring reasons. Guard against inflated
The FT reports Kimi K3 will be the largest open AI model from China, with a parameter count between 2 trillion and 3 trillion.
<p><strong>Tool:</strong> <a href="https://tools.simonwillison.net/grok-mermaid">Mermaid to Unicode box art (grok-mermaid)</a></p> <p>While <a href="https://simonwillison.net/2026/Jul/15/grok-build/">exploring the codebase</a> for the newly open-sourced Grok CLI coding agent I came across <a href="https://github.com/xai-org/grok-build/blob/b189869b7755d2b482969acf6c92da3ecfeffd36/crates/codegen/xai-grok-markdown/src/mermaid.rs">xai-grok-markdown/src/mermaid.rs</a>, a "self-contained terminal renderer for Mermaid diagrams" written in Rust.</p> <p>I figured it would be fun to try that out in a browser via WebAssembly. Here's <a href="https://github.com/simonw/tools/pull/293#issue-4897479396">the prompt</a> I ran in Claude Code for web (Fable 5), and this is what the resulting tool looks like:</p> <p><img alt="Screenshot of a Mermaid diagram editor showing source code and rendered flowchart. The code reads: graph TD Start[Request received] --> Auth{Authenticated?} Auth -->|yes| Rate{Rate limit OK?} Auth -->|no| R401[401 Unauthorized] Rate -->|yes| H(Handle request) Rate -->|no| R429[429 Too Many Requests] H -.-> Log[Audit log] H ==> Resp[200 OK]. Below the code are controls labeled Max width: Fit output panel, Copy as text, and Copy link to this diagram. The rendered flowchart on a dark background flows top-down: Request received leads to Authenticated?, which branches yes to Rate limit OK? and no to 401 Unauthorized. Rate limit OK? branches yes to Handle request and no to 429 Too Many Requests. Handle request connects with a dotted arrow to Audit log and a thick arrow to 200 OK." src="https://static.simonwillison.net/static/2026/grok-mermaid-wasm.png" /></p> <p>Tags: <a href="https://simonwillison.net/tags/tools">tools</a>, <a href="https://simonwillison.net/tags/rust">rust</a>, <a href="https://simonwillison.net/tags/webassembly">webassembly</a>, <a href="https://simonwillison.net/tags/mermaid">mermaid</a>, <a href="https://simonwillison.net/tags
If you’re in the market for a frontier-class open weights model, your options are few and far between outside of the Chinese model houses. With the Wednesday release of a new model code-named "Inkling", an outfit called Thinking Machines Lab aims to change that. Founded in early 2025 by former OpenAI CTO Mira Murati, Thinking Machines' first model is a big one. Weighing in at 975 billion parameters, the model requires more than two terabytes of GPU memory — a quantity present in around eight of Nvidia's B300 accelerators, or sixteen H200s — to run at its native 16-bit precision. If that’s asking too much of your hardware, Thinking Machines has also released a NVFP4 quantized version of the model capable of running on half the GPUs. This makes it the largest American open weights model to date, and comparable to Chinese models like DeepSeek V4, GLM 5.2, and Kimi K2.6 in terms of size and capabilities. Take these claims with a grain of salt — gaming AI benchmarks isn’t exactly difficult — but Thinking Machines says Inkling is competitive with these models in a variety of workloads, although its benchmark charts also show it trailing proprietary models like Anthropic’s Claude and OpenAI’s GPT. Thinking Machines describes the model as being highly adaptable, intended for use by developers building AI apps, but suitable for general purpose applications like chat bots. And because it’s being released under a highly permissive Apache 2.0 license, end users are free to fine tune it for their specific use case. The company's Tinker platform offers tools to do just that. In fact, Thinking Machines boasts that the model is capable of writing its own fine tuning scripts to refine its behavior, teach itself new skills, and evaluate its abilities. Other notable features include support for a million-token context, which you can think of as the model’s short-term memory. This should help it wrangle large code bases and needle-in-the-haystack type search problems. While Thinking Ma
Microsoft is looking to sell its in-house AI models as more efficient and cost-effective than its competitors' models.
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