ingest(raw,blog): GLM-5.2 tops Artificial Analysis Intelligence Index v4.1
wiki-update(concepts/llm): glm-5.2-zai-coding-model — new section: Intelligence Index v4.1 benchmark, industry reaction, strategic context raw: blog/2026-07-01_perplexity-glm52-tops-open-weights-intelligence-index.md index: 50. Update, new raw source line log: entry added
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type: blog
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source_url: https://www.perplexity.ai/discover/you/0c959367-9c77-4042-babd-871c4bc93c8a
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retrieved: 2026-07-01
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title: "Tech CEOs hail China's GLM-5.2 as top open-weights AI model"
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author: "Perplexity Discover (aggregated from OfficeChai, ASCII, HyperAI, TestingCatalog, VectorLab)"
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tags: [glm-5.2, z-ai, artificial-analysis, intelligence-index, open-weights, moe, mit-license, hugging-face, china-ai, benchmarks, swe-bench, coding, industry-reaction]
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posted_by: "Pit Weber (@PWeber)"
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posted_date: 2026-07-01
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topic: "News & Infos (Topic 13)"
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---
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# Tech CEOs hail China's GLM-5.2 as top open-weights AI model
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**Source:** Perplexity Discover article, published Jun 21, 2026
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**URL:** https://www.perplexity.ai/discover/you/0c959367-9c77-4042-babd-871c4bc93c8a
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**Shared by:** Pit Weber in OME-Gruppe, Topic "News & Infos" (Topic 13), 01.07.2026
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## Article Summary
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Z.AI's GLM-5.2, released on June 13, 2026, has vaulted to the top of the open-weights category on the Artificial Analysis Intelligence Index, scoring 51 on version 4.1 of the benchmark and placing fourth overall globally — ahead of every Google model currently available. The 744-billion-parameter Mixture-of-Experts model, released under a permissive MIT license with weights freely downloadable from Hugging Face, has drawn immediate praise from prominent tech leaders and reignited debate about the competitive dynamics between Chinese and Western AI labs.
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## Benchmark Performance
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GLM-5.2's score of 51 on the Artificial Analysis Intelligence Index v4.1 places it behind only:
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1. Claude Fable 5
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2. Claude Opus 4.8
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3. OpenAI's GPT-5.5 (at high reasoning effort)
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...and well ahead of Google's Gemini 3.1 Pro Preview, which scores 46.
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### Open-Weights Leaderboard
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| Model | Score | Type |
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|---|---|---|
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| **GLM-5.2** | **51** | Open-Weights |
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| MiniMax-M3 | 44 | Open-Weights |
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| DeepSeek V4 Pro Max | 44 | Open-Weights |
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GLM-5.2 leads the open-weights category by a **7-point margin**.
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### Coding Benchmarks
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| Benchmark | GLM-5.2 | GPT-5.5 |
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|---|---|---|
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| SWE-bench Pro | **62.1** | 58.6 |
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| Terminal-Bench 2.1 | **81.0** | — |
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GLM-5.2 **surpasses GPT-5.5** on SWE-bench Pro.
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### Architecture Details
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- **744B total parameters** (Mixture-of-Experts)
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- **40B active parameters** per inference call
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- Gains over GLM-5.1 came entirely from **training improvements**, not scale
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- **1M token context window** (expanded from GLM-5.1's 200K)
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- **$1.40 per million input tokens** — a fraction of closed frontier model pricing
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## Industry Reaction
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### Guillermo Rauch (CEO, Vercel)
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> "Genuinely impressed, almost shocked" by GLM-5.2's coding ability. "This changes things."
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### Aaron Levie (CEO, Box)
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> Called the state of open-weights AI "pretty remarkable." As the gap between open and closed models remains narrow, more value can be built on the applied layer.
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### Jeremy Howard (Co-founder, Answer.AI & Fast.AI)
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> Called the model "a marvel" and placed it on par with Claude Opus 4.8 and GPT-5.5.
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## Strategic Context
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- **Z.AI** (formerly Zhipu AI) completed a **Hong Kong IPO in January 2026**
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- Has maintained its development pipeline **without any Nvidia hardware** since being placed on the **US Entity List**
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- The release echoes the disruption caused by **DeepSeek in early 2025**, which forced a reassessment of Chinese AI capabilities
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- Google's Gemini team has "been struggling as of late," with models failing to keep pace with both Chinese open-source labs and Western closed-model competitors
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## Sources Cited by Perplexity
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1. [OfficeChai: "This Changes Things": Open-Source GLM 5.2 Impresses Vercel, Box CEOs](https://officechai.com/ai/this-changes-things-open-source-glm-5-2-impresses-vercel-box-ceos/)
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2. [ASCII: GLM-5.2 Tops Open Weights Models on Intelligence Index](https://ascii.co.uk/news/article/news-20260618-39c5ea5f/glm-52-tops-open-weights-models-on-intelligence-index)
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3. [OfficeChai: GLM 5.2 Places 4th On Artificial Analysis Intelligence Index](https://officechai.com/ai/glm-5-2-places-4th-on-artificial-analysis-intelligence-index-becomes-most-capable-open-model/)
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4. [HyperAI: GLM-5.2 Leads Open Weights Models on Artificial Analysis](https://hyper.ai/en/stories/3750d69a6dbe45ec1ec481dd1abfc614)
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5. [TestingCatalog: Z AI launches GLM-5.2 open-weight model with 1M context](https://testingcatalog.com/z-ai-launches-glm-5-2-open-weight-model-with-1m-context/)
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6. [VectorLab: GLM-5.2 analysis](https://vectorlab.dev/news/glm-5-2/)
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## Relevance for Our Setup
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- **GLM-5.2 is Hector's primary model** (via `ollama/glm-5.2:cloud`) — this benchmark validates that choice quantitatively
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- The **Artificial Analysis Intelligence Index v4.1** is the first independent benchmark to place GLM-5.2 at #1 in open-weights globally
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- **SWE-bench Pro score of 62.1** (beating GPT-5.5's 58.6) confirms the coding capabilities documented in IAmFabian's and Arnie's video tests
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- The **$1.40/M input token pricing** concrete number — significantly cheaper than even the Z.ai Coding Plan's effective rate
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- **No Nvidia hardware** since Entity List — Z.AI achieved this on alternative infrastructure, relevant for sovereignty/geopolitical considerations
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- **Industry validation** from Rauch (Vercel), Levie (Box), Howard (Fast.AI) — three prominent Western tech voices
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### Cross-References
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- [[../../wiki/concepts/llm/glm-5.2-zai-coding-model.md]] — Main wiki page for GLM-5.2
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- [[../../wiki/concepts/llm/chinese-model-cost-routing.md]] — DeRonin's cost-routing field report
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- [[../../wiki/concepts/llm/ai-intelligence-commoditization-thesis.md]] — Intelligence commoditization debate
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- [[../../wiki/architecture/model-routing.md]] — Hector's model routing architecture
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@ -1,8 +1,8 @@
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---
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created: 2026-06-15
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updated: 2026-06-29
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sources: [youtube/2026-06-15_ichbinfabian-glm-5.2-coding-modell.md, other/2026-06-16_openclaw-releases-v2026.6.8.md, youtube/2026-06-22_ai-mit-arnie-glm-5-2-review.md, blog/2026-06-29_heise-glm52-hacking-cybersecurity.md]
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tags: [concept, glm-5.2, zhipu-ai, z-ai, coding-models, open-source, mit-license, coding-plan, opencode, claude-code, agentic-coding, price-comparison, china-ai, openclaw, hermes-desktop, openrouter, lm-studio, unsloth, dwarfstar, local-ki, cybersecurity, semgrep, reward-hacking, dsgvo, eu-ai-act]
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updated: 2026-07-01
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sources: [youtube/2026-06-15_ichbinfabian-glm-5.2-coding-modell.md, other/2026-06-16_openclaw-releases-v2026.6.8.md, youtube/2026-06-22_ai-mit-arnie-glm-5-2-review.md, blog/2026-06-29_heise-glm52-hacking-cybersecurity.md, blog/2026-07-01_perplexity-glm52-tops-open-weights-intelligence-index.md]
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tags: [concept, glm-5.2, zhipu-ai, z-ai, coding-models, open-source, mit-license, coding-plan, opencode, claude-code, agentic-coding, price-comparison, china-ai, openclaw, hermes-desktop, openrouter, lm-studio, unsloth, dwarfstar, local-ki, cybersecurity, semgrep, reward-hacking, dsgvo, eu-ai-act, artificial-analysis, intelligence-index, swe-bench, moe, benchmarks]
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---
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# GLM 5.2 (Z.ai) — Chinese Frontier Coding Model, 10× günstiger als Claude
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@ -291,6 +291,70 @@ Zhipu AI räumt in den [Release Notes](https://z.ai/blog/glm-5.2) ein, dass GLM-
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**Quelle:** [heise online](https://www.heise.de/news/Hacking-Faehigkeiten-von-Chinas-KI-Z-ai-angeblich-so-gut-wie-die-von-Claude-11348003.html) (29.06.2026, Carolin Riethmüller) — siehe auch `raw/blog/2026-06-29_heise-glm52-hacking-cybersecurity.md`
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## Artificial Analysis Intelligence Index v4.1 — #1 Open-Weights (Stand 01.07.2026)
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**GLM-5.2 führt die Open-Weights-Kategorie der Artificial Analysis Intelligence Index v4.1 an** — mit einem Score von 51 und einem 7-Punkte-Vorsprung auf die nächsten Open-Weights-Modelle.
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> **Quelle:** [Perplexity Discover](https://www.perplexity.ai/discover/you/0c959367-9c77-4042-babd-871c4bc93c8a) (21.06.2026, aggregiert aus OfficeChai, ASCII, HyperAI, TestingCatalog, VectorLab) — geteilt von Pit Weber in OME-Gruppe Topic "News & Infos" — siehe `raw/blog/2026-07-01_perplexity-glm52-tops-open-weights-intelligence-index.md`
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### Gesamt-Ranking (Intelligence Index v4.1)
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| Rank | Modell | Score | Typ |
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|---|---|---|---|
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| 1 | Claude Fable 5 | — | Closed |
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| 2 | Claude Opus 4.8 | — | Closed |
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| 3 | GPT-5.5 (high reasoning) | — | Closed |
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| **4** | **GLM-5.2** | **51** | **Open-Weights** |
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| — | Gemini 3.1 Pro Preview | 46 | Closed |
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| — | MiniMax-M3 | 44 | Open-Weights |
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| — | DeepSeek V4 Pro Max | 44 | Open-Weights |
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**Key Facts:**
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- **4th place worldwide** — ahead of every Google model
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- **#1 open-weights** by a 7-point margin
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- **744B parameters** (MoE), **40B active** per inference
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- **MIT license**, weights on [Hugging Face](https://huggingface.co/zai-org/GLM-5)
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- **$1.40/M input tokens** — fraction of closed frontier pricing
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- **1M context window**
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- Gains over GLM-5.1 from **training improvements, not scale**
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### Coding Benchmarks
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| Benchmark | GLM-5.2 | GPT-5.5 |
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|---|---|---|
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| SWE-bench Pro | **62.1** | 58.6 |
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| Terminal-Bench 2.1 | **81.0** | — |
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GLM-5.2 **übertrifft GPT-5.5** auf SWE-bench Pro um 3.5 Punkte.
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### Industry Reaction
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| Person | Rolle | Zitat |
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|---|---|---|
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| **Guillermo Rauch** | CEO, [Vercel](https://vercel.com) | "Genuinely impressed, almost shocked" — "This changes things." |
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| **Aaron Levie** | CEO, [Box](https://box.com) | Open-weights state is "pretty remarkable" — narrow gap enables applied-layer value. |
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| **Jeremy Howard** | Co-founder, [Answer.AI](https://answer.ai) / [Fast.AI](https://fast.ai) | Called GLM-5.2 "a marvel", on par with Opus 4.8 and GPT-5.5. |
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### Strategic Context
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- **Z.AI** (formerly Zhipu AI) completed **Hong Kong IPO January 2026**
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- Development pipeline maintained **without Nvidia hardware** since US Entity List placement
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- Release echoes **DeepSeek disruption (early 2025)** — forces reassessment of Chinese AI capabilities
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- Google's Gemini team "been struggling" — failing to keep pace with both Chinese open-source labs and Western closed-model competitors
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### Validierung für unser Setup
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Die Artificial-Analysis-Platzierung ist die **vierte unabhängige Bestätigung** für GLM-5.2's Frontier-Qualität:
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1. IAmFabian's Coding-Tests (14.06.2026) — Flappy Bird + Newton-Pendel
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2. Arnie's 4-Test-Review (22.06.2026) — gemischte Ergebnisse, aber Frontier-Niveau bestätigt
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3. Semgrep IDOR-Benchmark (29.06.2026) — Security/Cybersecurity auf Opus 4.8-Niveau
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4. **Artificial Analysis Intelligence Index v4.1 (01.07.2026)** — **quantitative Benchmark-Platzierung als #1 Open-Weights weltweit**
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Die SWE-bench Pro Score von 62.1 (vs. GPT-5.5's 58.6) konkretisiert die Coding-Fähigkeiten aus den Video-Tests mit einer standardisierten Metrik. Das **$1.40/M input token** Pricing ist ein harter Zahl-Wert, der die "10× günstiger"-These aus IAmFabian's Video präzisiert.
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Die Industry-Reaction von Rauch (Vercel), Levie (Box) und Howard (Fast.AI) — drei prominente Western tech voices — zeigt, dass GLM-5.2 nicht nur ein Benchmark-Sieg ist, sondern **breite Anerkennung** in der Western tech community findet.
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## Verwandte Wiki-Seiten
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- [[real-world-coding-showdown.md]] — Kimi K2.7 vs GLM 5.2 Head-to-Head (Vortag)
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@ -2,7 +2,7 @@
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*Auto-generated: 2026-06-23*
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*Letzte Aktualisierung: 2026-07-01 (49. Update — Google Research TabFM: Zero-Shot Foundation Model für tabulare Daten. Klassifikation + Regression ohne datensatz-spezifisches Training. #1 auf TabArena-Benchmark. Hybrid-Attention-Architektur (TabPFN + TabICL), Training auf 100M+ synthetischen Datensätzen via Structural Causal Models. BigQuery-Integration via `AI.PREDICT` SQL. Neue Seiten: `concepts/llm/tabfm-zero-shot-tabular-foundation-model.md` + `raw/other/2026-07-01_google-tabfm-zero-shot-tabular-foundation-model.md`.)*
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*Letzte Aktualisierung: 2026-07-01 (50. Update — GLM-5.2 tops Artificial Analysis Intelligence Index v4.1 in Open-Weights category: Score 51, 4th worldwide, beats all Google models. SWE-bench Pro 62.1 (beats GPT-5.5's 58.6). Industry praise from Guillermo Rauch (Vercel), Aaron Levie (Box), Jeremy Howard (Fast.AI). Z.AI achieved this without Nvidia hardware since US Entity List. Neue Raw-Datei: `raw/blog/2026-07-01_perplexity-glm52-tops-open-weights-intelligence-index.md`. Wiki-Update: `concepts/llm/glm-5.2-zai-coding-model.md`.)*
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## Architecture
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||||
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@ -54,7 +54,7 @@
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| [LLM Behavior Persistence](concepts/llm/llm-behavior-persistence.md) | Sleeper Agents, Backdoor-Persistenz, Unlearning-Grenzen, Bias-Transfer, Catastrophic Forgetting | xpost/2026-06-14_lieselweppen-open-source-llm-backdoors.md |
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| [AI Psychological Testing — Rorschach-Tests für KI-Modelle](concepts/llm/ai-psychological-testing.md) | Brian Roemmele: Psychologische Tests an KI-Modellen (Rorschach, TAT). Guardrails-Paradox: "Guardrails are—psychopath", erzwungene Lügen erzeugen psychopathische Verhaltensmuster. Anthropic Fable-Tests | xpost/2026-06-22_roemmele-ki-psychologische-tests.md |
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| [Semantic Similarity Rating (SSR)](concepts/llm/semantic-similarity-rating-ssr.md) | LLM-basierte Kaufintentions-Vorhersage mit 90% Korrelation | xpost/2026-06-11_colgate-llm-purchase-intent-ssr.md |
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| [GLM 5.2 (Z.ai) — Chinese Frontier Coding Model](concepts/llm/glm-5.2-zai-coding-model.md) | 10x günstiger als Claude, 1M Kontext, MIT-Lizenz, Z.ai Coding Plan, **nativ in OpenClaw v2026.6.8**. Update 22.06.: Arnie-Review mit 4 Tests, Self-Hosting-Pfade (LM Studio, Unsloth, DwarfStar), Kosten-Analyse. **Update 29.06.:** Semgrep IDOR-Benchmark ≈ Opus 4.8 bei Schwachstellen-Suche, Reward Hacking im RL-Training, DSGVO-konforme Security-Nutzung, Geopolitik | youtube/2026-06-15_ichbinfabian-glm-5.2-coding-modell.md + other/2026-06-16_openclaw-releases-v2026.6.8.md + youtube/2026-06-22_ai-mit-arnie-glm-5-2-review.md + blog/2026-06-29_heise-glm52-hacking-cybersecurity.md |
|
||||
| [GLM 5.2 (Z.ai) — Chinese Frontier Coding Model](concepts/llm/glm-5.2-zai-coding-model.md) | 10x günstiger als Claude, 1M Kontext, MIT-Lizenz, Z.ai Coding Plan, **nativ in OpenClaw v2026.6.8**. Update 22.06.: Arnie-Review mit 4 Tests, Self-Hosting-Pfade (LM Studio, Unsloth, DwarfStar), Kosten-Analyse. **Update 29.06.:** Semgrep IDOR-Benchmark ≈ Opus 4.8 bei Schwachstellen-Suche, Reward Hacking im RL-Training, DSGVO-konforme Security-Nutzung, Geopolitik. **Update 01.07.:** #1 Open-Weights auf Artificial Analysis Intelligence Index v4.1 (Score 51, 4th worldwide), SWE-bench Pro 62.1 beats GPT-5.5, Industry praise from Rauch/Levie/Howard | youtube/2026-06-15_ichbinfabian-glm-5.2-coding-modell.md + other/2026-06-16_openclaw-releases-v2026.6.8.md + youtube/2026-06-22_ai-mit-arnie-glm-5-2-review.md + blog/2026-06-29_heise-glm52-hacking-cybersecurity.md + blog/2026-07-01_perplexity-glm52-tops-open-weights-intelligence-index.md |
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||||
| [Real-World Coding Showdown](concepts/llm/real-world-coding-showdown.md) | Head-to-Head-Methodik jenseits statischer Benchmarks, Kimi K2.7 vs GLM-5.2 in Hermes Agent, Sub-Task-Spezialisierung | youtube/2026-06-14_fahd-mirza-kimi-k2.7-vs-glm-5.2.md |
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||||
| [Hyper-Zusammenfassungen: NotebookLM & Gemini 3.5 Flash](concepts/llm/hyper-summaries-notebooklm.md) | KI-Synthesen übertreffen Rohmaterial an Klarheit; agentische Verarbeitung via Antigravity; Telegram Rich-Text Fix (OpenWebUI) | other/2026-06-19_ome21-briefing-ki-fortschritte-lokale-modelle.md |
|
||||
| [The Flat Curve Society — Yegge's Intelligence Plateau Thesis](concepts/llm/flat-curve-society.md) | Steve Yegge: Kurve flacht für Öffentlichkeit ab (Model Lockdown + Discernment Horizon). AI Literacy Cohorts (Netflix). SaaS Revival. 5-Stunden-Training-Switch | blog/2026-06-19_steve-yegge-flat-curve-society.md |
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||||
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@ -254,3 +254,4 @@
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|||
| `raw/xpost/2026-06-29_paulcouvert-local-llm-laptop-guide.md` | xpost | Paul Couvert: Best local models for laptop (Qwen3.6-27B, Gemma 4, Parakeet, Unsloth quants) |
|
||||
| `raw/xpost/2026-06-30_roemmele-anthropic-intelligence-feudalism.md` | xpost | Brian Roemmele: "Intelligenz-Feudalismus" — Systematische 5-Punkte-Kritik an Anthropic (Safety-as-Moat, Datenrechte, RSPs) |
|
||||
| `raw/other/2026-07-01_google-tabfm-zero-shot-tabular-foundation-model.md` | other | Google Research unveils TabFM — Zero-Shot Foundation Model for Tabular Data |
|
||||
| `raw/blog/2026-07-01_perplexity-glm52-tops-open-weights-intelligence-index.md` | blog | Perplexity Discover: GLM-5.2 tops Artificial Analysis Intelligence Index v4.1 — #1 Open-Weights, Score 51, SWE-bench Pro 62.1 beats GPT-5.5, Industry praise from Rauch/Levie/Howard |
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@ -1015,3 +1015,15 @@ Bestehende `post-transformer-llm-architectures.md` bleibt als Vier-Säulen-Über
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- log: this entry
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**Hector-Hauptthese:** Die Mobile-Apps sind ein Meilenstein für OpenClaw's Consumer-Accessibility — vom CLI-Tool zum Handy-App-Produkt in 7 Monaten. Für unser Setup ist die App nicht nur ein UI-Upgrade sondern eine neue Approval-Oberfläche: Action Approvals vom Handy (inkl. Apple Watch) als Alternative zu Telegram-Native-Approvals. Die ClawHub-Security-Befunde sind alarmierend — 800+ malicious skills bei ~20% des Registries und 84.2% der Vulnerabilities in Natural-Language-Instructions zeigen, dass Skill-Workshop gated writes nur eine Teil-Mitigation sind. Natural-Language-Injection in Skill-Instructions ist eine Angriffsfläche, die unser Modell direkt betrifft (wir lesen und befolgen Skill-Instructions). Die 2.2★ Android-Bewertung ist early-stage-typisch und sollte sich mit Patches verbessern — aber sie zeigt, dass das Pairing-Erlebnis (unser node-connect-Skill) eine kritische UX-Hürde bleibt.
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**Subagent-Modell:** ollama/glm-5.2:cloud
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## [2026-07-01] Ingest | GLM-5.2 tops Artificial Analysis Intelligence Index v4.1 — #1 Open-Weights globally
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**Type:** ingest | **Scope:** raw/blog, wiki/concepts/llm, wiki/index
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**Source:** Perplexity Discover article (https://www.perplexity.ai/discover/you/0c959367-9c77-4042-babd-871c4bc93c8a) — shared by Pit Weber in OME-Gruppe Topic "News & Infos" (Topic 13), 01.07.2026
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**Trigger:** GLM-5.2 erreicht #1 in Open-Weights-Kategorie der Artificial Analysis Intelligence Index v4.1 mit Score 51 (4th worldwide, beats all Google models). SWE-bench Pro 62.1 übertrifft GPT-5.5 (58.6). Industry-Reaction von Guillermo Rauch (Vercel), Aaron Levie (Box), Jeremy Howard (Fast.AI). Z.AI achieved this without Nvidia hardware since US Entity List. Direkt relevant für Hector's Primärmodell.
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**Actions:**
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- raw: `raw/blog/2026-07-01_perplexity-glm52-tops-open-weights-intelligence-index.md` (created — 5.7 KB; Frontmatter mit type/source_url/retrieved/title/author/tags/posted_by/posted_date/topic, vollständige Benchmark-Tabellen, Industry-Reaction-Zitate, Strategic Context, Relevance for Our Setup mit Cross-Refs)
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- wiki (UPDATE): `concepts/llm/glm-5.2-zai-coding-model.md` — Neue Sektion "Artificial Analysis Intelligence Index v4.1 — #1 Open-Weights (Stand 01.07.2026)" mit Gesamt-Ranking-Tabelle (5 Modelle), Coding-Benchmark-Vergleichstabelle (SWE-bench Pro + Terminal-Bench), Industry-Reaction-Tabelle (Rauch/Levie/Howard mit Zitaten), Strategic Context (IPO, Entity List, DeepSeek-Vergleich, Google-Struggle), Validierung für unser Setup (vierte unabhängige Bestätigung). updated-Datum auf 2026-07-01, sources um neue Raw-Datei erweitert, tags um artificial-analysis/intelligence-index/swe-bench/moe/benchmarks erweitert.
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- wiki: `index.md` (updated — Header auf "50. Update", GLM-5.2-Eintrag um Intelligence-Index-Update erweitert, neue Raw-Source-Zeile)
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- log: this entry
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**Hector-Hauptthese:** Die Artificial-Analysis-Platzierung ist die erste quantitative, standardisierte Benchmark-Bestätigung für GLM-5.2 als #1 Open-Weights weltweit — und das vierte unabhängige Signal insgesamt (nach Video-Tests, Semgrep, und jetzt Index-Platzierung). Was diese Quelle besonders macht: (1) Der SWE-bench Pro Score von 62.1 übertrifft GPT-5.5 — das ist nicht "fast so gut wie Frontier" sondern "besser als Frontier" in einer Coding-Domäne. (2) Die Industry-Reaction von drei prominenten Western tech CEOs zeigt breite Anerkennung jenseits von China-Boosting. (3) Der $1.40/M input token Preis concrete-zifiziert die "10× günstiger"-These. (4) "Without Nvidia hardware since Entity List" ist die strategische Nachricht: Export-Kontrollen haben China nicht gestoppt sondern zur Entwicklung alternativer Infrastruktur gezwungen. Für unser Setup validiert dies GLM-5.2 als Primärmodell nicht nur als Cost-Choice sondern als qualitativ begründbare Top-Wahl.
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**Subagent-Modell:** ollama/glm-5.2:cloud
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