Every week, I organize 400 to 700 links into roughly 60 categories as part of my ongoing effort to learn about AI. This is my personal notebook, which I enjoy sharing with friends… a hobby and a labor of love, rather than a commercial publication or product.
If you arrived here through a search or shared link, this page collects the links I found for Zhipu AI for the week ending August 21, 2026.
As part of my learning process, I like to automate the category covers. It gives me a chance to learn Python and APIs.
This week’s cover prompt was written using Claude Opus 4.7, and the image was generated using Nano Banana 2.1.
Category Cover Image Prompt: { "category": "Zhipu AI", "short_title": "Shanghai Deco Herm with Knowledge Scroll", "concept_description": "A warm limestone Art Deco tower in 1930s Shanghai, where a stylized herm emerges from a corner pier holding a tightly rolled scroll stamped with a carved Deco seal of interlocking geometric glyphs, suggesting a knowledge graph rendered in 1929 sculptural language. The figure wears a simplified geometric cap, its drapery falling into chevrons that merge into the pier below. Across the lintel beneath the setback, the inscription ZHIPU AI is cut deep into the stone, catching the raking afternoon sun.", "image_prompt": "Realistic architectural photograph of a 1930s honey-cream limestone Art Deco skyscraper on a bright sunny day in old Shanghai, with a stylized engaged herm carved into a corner pier at a setback, holding a rolled stone scroll stamped with a geometric Deco seal of interlocking glyphs against its chest, wearing a simplified chevron cap and drapery that narrows into the masonry below. The words ZHIPU AI are incised in large Deco capitals across the lintel beneath the figure, deep blue sky above, neighboring 1930s buildings receding behind, crisp raking sunlight casting sharp shadows across the carving. }
This Week in Zhipu AI News
Summary by Claude Sonnet 5.5 based on this week’s links:
- GLM-5.3 lands near the top of open models: Zhipu's GLM-5.3 scored 60 on the Artificial Analysis Intelligence Index, up 7 points from GLM-5.2 and tied with Kimi K3. Arena placed GLM-5.3 (Max) at #2 among open models on WebDev, and Vals AI had it #2 on Terminal Bench.
- Post-training did the heavy lifting: A Zhihu breakdown argues the gains come mostly from post-training, since GLM-5.3 appears to reuse GLM-5.2's 743B MoE base. A Zhipu researcher separately highlighted SAO, an asynchronous reinforcement learning method released alongside GLM-5.2. The founder's own framing was that scaling is not over, but data, inference compute and post-training matter as much as model size.
- Same price, aimed at agents: The GLM-5.3 API is live at the same price as GLM-5.2, reported by VentureBeat as $1.4 input and $4.4 output per million tokens. Zhipu pitches it for coding, defensive cybersecurity and long agentic tasks, and also promotes AutoClaw, its agent product for finishing work tasks.
This summary was generated by Claude Sonnet 5.5 to help you explore the links below. Rest assured, I select, organize, and check the links by hand in Google Sheets, and write the introduction and personal commentary in The Main Newsletters myself each week as a labor of love.
This week's links related to Zhipu AI
GLM-5.3: Frontier Coding with Emergent Cyber Capabilities
https://z.ai/blog/glm-5.3
Interesting take by the zAI (GLM-Models) founder: AI scaling is not over, but we just focused too much on model size. For years, the industry mostly asked: How many parameters does a model have? But performance also depends on training data, inference compute and post-training.”
https://x.com/kimmonismus/status/2090026799916888080
@WanHL7 @aquilesfd Theyre all bigger than that, imo. Opus is ~1.5-2T and Fable is ~5-7T. Sonnet is GLM sized (~600-800b). And haiku is probably ~200-350b. Anthropic is better at making Big models but worse at making small models than OAI.”
https://x.com/jmbollenbacher/status/2089712688096022619
The real benchmark for an AI agent isn’t what it says. It’s what it gets done. AutoClaw, @Zai_org ‘s AI Agent for Work, is built to turn intent into finished output. Give it a complex task. AutoClaw breaks it down, operates tools, works across files, coordinates multiple”
https://x.com/AutoClawAIer/status/2090446256342708724
Great to see so much interest in our post-training work. Want to reshare SAO (Single-Rollout Asynchronous Optimization), a key recent advance in agentic reinforcement learning alongside GLM-5.2. SAO tackles the off-policy and stability challenges of asynchronous RL through: -“
https://x.com/ZixuanLi_/status/2090564295696306436
GLM-5.3 API is now live. – Built for coding, defensive cybersecurity, and long-horizon agentic tasks – Priced the same as GLM-5.2 – Available via the official API and partner model gateways Get started:
https://x.com/Zai_org/status/2089816129011098048
GLM-5.3 (Max) by @Zai_org has shifted the Pareto frontier for Code Arena: WebDev! GLM-5.3 (Max) would sit at #2 among open models (upon open weights release, and #8 overall) with 1597 pts in the Code Arena: WebDev. At $3.65/M, GLM-5.3 (Max) is on par with Qwen3.8 (Max)”
https://x.com/arena/status/2090581559262798055
GLM 5.3 is #2 on Terminal Bench, #3 on Legal Bench, and #6 on Skills Bench among-open weight models.”
https://x.com/ValsAI/status/2090192848780136668
GLM-5.3 achieves 60 on the Artificial Analysis Intelligence Index, on par with Kimi K3 and up 7 points from GLM-5.2. Once the weights are released it will be tied as the leading open weights model @Zai_org has just launched GLM-5.3, which ties Kimi K3 (60) for the most”
https://x.com/ArtificialAnlys/status/2089830890709135426
GLM-5.3: How Chinese labs keep stride with the frontier
https://www.interconnects.ai/p/glm-53-how-chinese-labs-keep-stride
GLM-5.3’s Biggest Upgrade Isn’t the Base Model. It’s the Post-Training Stack. A technical breakdown from Zhihu contributor 欠阿贝尔两块钱 on why GLM-5.3’s gains appear to come largely from post-training scaling… not a new backbone. TL;DR: GLM-5.3 reuses GLM-5.2’s 743B MoE base”
https://x.com/ZhihuFrontier/status/2089977451627847789
GLM-5.3 hits the API at $1.4/$4.4 per million tokens | VentureBeat
https://venturebeat.com/ai/glm-5-3-hits-the-api-at-1-4-4-4-per-million-tokens
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