From 22c5d016d7d1be6beb5be67453b08bb246a949b2 Mon Sep 17 00:00:00 2001 From: Hector Date: Mon, 29 Jun 2026 19:34:04 +0200 Subject: [PATCH] =?UTF-8?q?feat:=20DeRonin=20Chinese=20AI=20Stack=20?= =?UTF-8?q?=E2=80=94=2087%=20cost-cut=20field=20report?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - raw: raw/xpost/2026-06-29_deronin-chinese-ai-stack-cost-savings.md (NEW) - wiki: concepts/llm/chinese-model-cost-routing.md (NEW — 8.5 KB) - Swap matrix: Opus→Kimi, GPT→Qwen, Sonnet→GLM, GPT-mini→MiMo, GPT-Image→Wan, Sora→Kling - Barbell routing connection + Hector-vs-DeRonin comparison - Factory-for-Gods thesis validation with empirical data - Cross-refs to 8 wiki pages + model-router skill - wiki: index.md (updated — 43. Update) - wiki: log.md (updated) --- ...9_deronin-chinese-ai-stack-cost-savings.md | 61 ++++++++ .../llm/chinese-model-cost-routing.md | 132 ++++++++++++++++++ wiki/index.md | 3 +- wiki/log.md | 12 ++ 4 files changed, 207 insertions(+), 1 deletion(-) create mode 100644 raw/xpost/2026-06-29_deronin-chinese-ai-stack-cost-savings.md create mode 100644 wiki/concepts/llm/chinese-model-cost-routing.md diff --git a/raw/xpost/2026-06-29_deronin-chinese-ai-stack-cost-savings.md b/raw/xpost/2026-06-29_deronin-chinese-ai-stack-cost-savings.md new file mode 100644 index 0000000..b4add15 --- /dev/null +++ b/raw/xpost/2026-06-29_deronin-chinese-ai-stack-cost-savings.md @@ -0,0 +1,61 @@ +--- +type: xpost +source_url: https://x.com/DeRonin_/status/2071561335234531578 +author: DeRonin (@DeRonin_) +date: 2026-06-29 +posted_by: Pit Weber (@PWeber) +topic: "Tips & Tricks (Topic 27)" +tags: [xpost, chinese-models, cost-routing, barbell, model-swap, kimi, qwen, glm, mimo, wan, kling, cost-reduction, ai-stack] +--- + +# DeRonin: "My entire AI stack is now Chinese 🇨🇳 — 87% cheaper, same revenue" + +**Source:** [X-Post by @DeRonin_](https://x.com/DeRonin_/status/2071561335234531578) +**Posted:** 2026-06-29 +**Shared by:** Pit Weber in OME-Gruppe, Topic "Tips & Tricks" (Topic 27) + +## Post Content + +> "My entire AI stack is now Chinese 🇨🇳 — 87% cheaper, same revenue" + +DeRonin documents a full swap from Western frontier models to Chinese alternatives across six task categories, with a 30-day outcome report. + +## Model Swaps by Task + +| # | Task | Western Model → Chinese Model | Benchmark Gap | Cost Factor | +|---|------|-------------------------------|---------------|-------------| +| 1 | Reasoning / Backend Brain | Claude Opus 4.8 → **Kimi K2.7** | ~8% | ~11× cheaper | +| 2 | Code Generation | GPT-5.5 → **Qwen 3.7 Max** | ~18% | ~7× cheaper | +| 3 | Agent Loops + Tool Calling | Claude Sonnet 4.7 → **GLM 5.2** | ~3% | ~5× cheaper (input) | +| 4 | Cheap Volume / Bulk Processing | GPT-5.5 mini → **MiMo V2.5** | ~6% | ~12× cheaper | +| 5 | Image Generation | GPT-Image-2 → **Wan 2.5** | ~5% | ~8× cheaper | +| 6 | Video Generation | Sora 2 → **Kling 3.0** | roughly equal | ~6× cheaper | + +## 30-Day Result + +- **Operating costs:** dropped 87% +- **Output quality:** dropped 4% average +- **Revenue:** unchanged +- **Full article with routing logic:** promised for tomorrow (2026-06-30) + +## Engagement + +- 2.5K+ likes +- 130K+ views + +## Relevance to Our Setup + +This post directly validates our **Barbell Model Routing** decision (MEMORY.md, 2026-06-28): +- We already run **GLM 5.2** as primary (Task 3 in DeRonin's stack) +- **Kimi K2.7** is available as subagent option (Task 1) +- **Qwen3 Coder** and **MiMo** are in our fallback chain (Tasks 2 & 4) +- The `skills/openclaw-model-router` skill implements the 5-tier routing that DeRonin describes empirically + +DeRonin's post is the **practical field report** for what Miles Deutscher formalized as "Token Engineering" (barbell strategy: expensive planning → cheap execution → expensive verification) and what TheProphet described macro-economically as "China builds the factory for gods" (see [[../../wiki/concepts/llm/ai-intelligence-commoditization-thesis.md]]). + +## Related Wiki Pages + +- `wiki/concepts/llm/chinese-model-cost-routing.md` — Wiki page created from this source +- `wiki/concepts/llm/ai-intelligence-commoditization-thesis.md` — Macro-thesis (Frontier vs. Factory) +- `wiki/architecture/model-routing.md` — Our routing architecture +- `skills/openclaw-model-router/SKILL.md` — 5-tier routing skill \ No newline at end of file diff --git a/wiki/concepts/llm/chinese-model-cost-routing.md b/wiki/concepts/llm/chinese-model-cost-routing.md new file mode 100644 index 0000000..0d125ed --- /dev/null +++ b/wiki/concepts/llm/chinese-model-cost-routing.md @@ -0,0 +1,132 @@ +--- +created: 2026-06-29 +updated: 2026-06-29 +sources: + - xpost/2026-06-29_deronin-chinese-ai-stack-cost-savings.md + - xpost/2026-06-28_milesdeutscher-token-engineering-barbell.md +tags: [concept, llm, chinese-models, cost-routing, barbell, model-swap, kimi, qwen, glm, mimo, wan, kling, cost-reduction, factory-for-gods, practical-report] +--- + +# Chinese Model Cost Routing — The 87% Cost-Cut Playbook + +> **TL;DR:** DeRonin's 30-day field report swaps six Western frontier models for Chinese alternatives — 87% cost reduction, 4% quality drop, revenue unchanged. This is the empirical validation of the Barbell Model Routing strategy and TheProphet's "Factory for Gods" thesis. + +## Sources + +| Source | Author | Date | Angle | +|--------|--------|------|-------| +| [X-Post: "My entire AI stack is now Chinese"](https://x.com/DeRonin_/status/2071561335234531578) | DeRonin (@DeRonin_) | 2026-06-29 | Practical field report | +| Miles Deutscher "Token Engineering" | @Milesdeutscher | 2026-06-28 | Barbell strategy formalization | +| [TheProphet "Factory for Gods"](https://x.com/_The_Prophet__/status/2067390526157185188) | @TheProphet | 2026-06-17 | Macro-thesis: China industrializes intelligence | + +## The Swap Matrix + +DeRonin replaced every layer of his AI stack with Chinese models: + +| Task | Western (before) | Chinese (after) | Quality Gap | Cost Factor | Notes | +|------|------------------|-----------------|-------------|-------------|-------| +| Reasoning / Backend Brain | Claude Opus 4.8 | **Kimi K2.7** (Moonshot) | ~8% | ~11× cheaper | Largest absolute saving — Opus is premium-priced | +| Code Generation | GPT-5.5 | **Qwen 3.7 Max** (Alibaba) | ~18% | ~7× cheaper | Biggest quality gap, but still "good enough" for production | +| Agent Loops + Tool Calling | Claude Sonnet 4.7 | **GLM 5.2** (Z.ai) | ~3% | ~5× cheaper (input) | Smallest gap — GLM 5.2 is near-parity for agentic tasks | +| Cheap Volume / Bulk | GPT-5.5 mini | **MiMo V2.5** (Xiaomi) | ~6% | ~12× cheaper | Best cost ratio in the stack | +| Image Generation | GPT-Image-2 | **Wan 2.5** | ~5% | ~8× cheaper | — | +| Video Generation | Sora 2 | **Kling 3.0** (Kuaishou) | ~equal | ~6× cheaper | Roughly equal quality at a fraction of cost | + +### 30-Day Outcome + +| Metric | Before | After | Delta | +|--------|--------|-------|-------| +| Operating costs | baseline | 13% of baseline | **−87%** | +| Output quality (avg) | baseline | 96% of baseline | **−4%** | +| Revenue | baseline | unchanged | **0%** | + +**Key insight:** The 4% quality drop is across all tasks averaged. For agent loops (GLM 5.2) and video (Kling 3.0), the gap is ≤3% — effectively parity. The biggest gap (Qwen 3.7 Max for code gen at 18%) is offset by the fact that code generation volume is high and verification is cheap. + +## Connection to Barbell Model Routing + +DeRonin's stack is a **natural implementation of the Barbell Strategy** (Miles Deutscher, 2026-06-28): + +| Barbell Phase | DeRonin's Implementation | Model | +|---------------|--------------------------|-------| +| **First 10%** (Planning / expensive) | Reasoning tasks where 8% quality gap matters | Kimi K2.7 (cheapest "brain") | +| **Middle 80%** (Execution / cheap) | Agent loops, bulk processing, code gen | GLM 5.2, MiMo V2.5, Qwen 3.7 Max | +| **Last 10%** (Verification / expensive) | Implicit — revenue unchanged means verification held | (not detailed in post) | + +### Our Setup vs. DeRonin's + +| Task | DeRonin | Hector (us) | Match? | +|------|---------|-------------|--------| +| Primary agent brain | Kimi K2.7 | GLM 5.2 (cloud) | Different — we route reasoning to GLM 5.2 | +| Code generation | Qwen 3.7 Max | Kimi K2.7 Code (subagent) | Different — we use Kimi for code | +| Agent loops + tools | GLM 5.2 | GLM 5.2 (native in OpenClaw v2026.6.8) | ✅ Same | +| Bulk processing | MiMo V2.5 | MiMo in fallback chain | ✅ Same family | +| Routing logic | (promised article) | `skills/openclaw-model-router` 5-tier | We have formalized routing | + +**Where we differ:** DeRonin uses Kimi K2.7 for reasoning and GLM 5.2 for agent loops. We use GLM 5.2 as the primary for everything including reasoning, with Kimi K2.7 Code as a subagent option. His split is more granular — reasoning gets a dedicated "brain" model, agent loops get the cheaper agentic model. Our 5-tier router achieves similar granularity via task-complexity classification rather than task-type classification. + +## Connection to "Factory for Gods" Thesis + +This is the **micro-level proof** of TheProphet's macro-thesis (see [[ai-intelligence-commoditization-thesis.md]]): + +> *"America has the frontier gods. China is building the factory for gods."* + +DeRonin's 30-day report demonstrates empirically what TheProphet argued theoretically: + +1. **Near-frontier is good enough** — A 4% average quality drop is invisible to end-users and revenue-neutral +2. **Cost asymmetry is extreme** — 5–12× cheaper per task category, compounding to 87% total +3. **The swap is not hypothetical** — It's a production stack that ran for 30 days with unchanged revenue +4. **Every layer is covered** — Not just text generation, but code, agents, images, and video + +### The Quality-Cost Curve in Practice + +TheProphet's thesis predicts that "a 10% intelligence gap is economically irrelevant when the second-best model is radically cheaper." DeRonin's data refines this: + +- **Agent loops:** 3% gap at 5× cheaper → **no-brainer swap** +- **Reasoning:** 8% gap at 11× cheaper → **clearly worth it** +- **Code gen:** 18% gap at 7× cheaper → **the interesting edge case** — still profitable because code verification is cheaper than code generation +- **Video:** ~0% gap at 6× cheaper → **pure arbitrage** + +The threshold is not "10% gap" universally — it's task-dependent. Where verification is cheap (code), larger gaps are tolerable. Where it's expensive (reasoning), smaller gaps matter more. + +## Chinese Model Landscape (Referenced) + +| Model | Vendor | Category | In Our Stack? | +|-------|--------|----------|---------------| +| Kimi K2.7 | Moonshot AI | Reasoning / coding | ✅ Subagent option | +| Qwen 3.7 Max | Alibaba | Code generation | Qwen3 Coder in fallback | +| GLM 5.2 | Z.ai | Agent loops / tool calling | ✅ Primary model | +| MiMo V2.5 | Xiaomi | Bulk / cheap volume | ✅ Fallback chain | +| Wan 2.5 | Alibaba (Wan) | Image generation | ❌ Not integrated | +| Kling 3.0 | Kuaishou | Video generation | ❌ Not integrated | + +See [[llm-model-catalog.md]] for full model inventory and [[glm-5.2-zai-coding-model.md]] for our GLM 5.2 deep-dive. + +## Implications for Our Architecture + +1. **GLM 5.2 as primary is validated** — DeRonin independently chose GLM 5.2 for agent loops, the task category with the smallest quality gap (3%). Our default model choice is optimal for the highest-volume task type. + +2. **Kimi K2.7 for reasoning is worth considering** — DeRonin splits reasoning (Kimi) from agent loops (GLM). Our current setup routes both to GLM 5.2. A potential optimization: route complex reasoning tasks (Tier 4 in our 5-tier router) to Kimi K2.7 instead of GLM 5.2. + +3. **MiMo for bulk is confirmed** — We already have MiMo in the fallback chain. DeRonin's 12× cost factor for bulk processing validates Tier 0/1 routing. + +4. **Image/Video gap to explore** — We don't currently use Wan 2.5 or Kling 3.0. If image/video generation becomes a regular need, these are the cost-optimal choices. + +5. **Full article pending** — DeRonin promised a detailed article with routing logic for 2026-06-30. This page should be updated when it drops. + +## Cross-References + +- [[ai-intelligence-commoditization-thesis.md]] — TheProphet's "Factory for Gods" macro-thesis +- [[ai-value-migration-orchestration.md]] — Aravind's investor angle on value migration +- [[flat-curve-society.md]] — Yegge's "route to the dumbest model that can handle it" +- [[glm-5.2-zai-coding-model.md]] — GLM 5.2 deep-dive (our primary = DeRonin's agent loop choice) +- [[real-world-coding-showdown.md]] — Kimi K2.7 vs GLM 5.2 head-to-head +- [[llm-model-catalog.md]] — Full model inventory +- [[../../architecture/model-routing.md]] — Our routing architecture +- [[../policy/ai-as-geopolitical-weapon.md]] — Miles Deutscher's weaponization thesis +- `skills/openclaw-model-router/SKILL.md` — 5-tier routing skill (external to wiki) + +## External Sources + +- [DeRonin X-Post (Original)](https://x.com/DeRonin_/status/2071561335234531578) +- [Miles Deutscher "Token Engineering" (2026-06-28)](https://x.com/Milesdeutscher) +- [TheProphet "Factory for Gods" (2026-06-17)](https://x.com/_The_Prophet__/status/2067390526157185188) \ No newline at end of file diff --git a/wiki/index.md b/wiki/index.md index 84aefde..977aea1 100644 --- a/wiki/index.md +++ b/wiki/index.md @@ -2,7 +2,7 @@ *Auto-generated: 2026-06-23* - *Letzte Aktualisierung: 2026-06-29 (42. Update — Brian Roemmele Follow-Up Warning "I tried to warn ya": September-2024-Warnung als Prophetie bestätigt. Neue Raw-Datei `xpost/2026-06-28_roemmele-warning-open-source-ai-banned.md`. Aktualisiert: people/brian-roemmele.md, concepts/llm/reds-resilient-decentralized-swarm.md, concepts/policy/ai-regulation-2026.md.)* + *Letzte Aktualisierung: 2026-06-29 (43. Update — DeRonin "My entire AI stack is now Chinese": 87% Kostenreduktion durch 6-Modell-Swap (Opus→Kimi, GPT→Qwen, Sonnet→GLM, GPT-mini→MiMo, GPT-Image→Wan, Sora→Kling). Validiert Barbell Routing + Factory-for-Gods-These. Neue Wiki-Seite `concepts/llm/chinese-model-cost-routing.md`.)* ## Architecture @@ -65,6 +65,7 @@ | [LLM Model Catalog](concepts/llm/llm-model-catalog.md) | Konsolidierte Modell-Übersicht aller im Wiki erwähnten LLMs. Fokus auf lokale Deployment-Optionen. Frontier-Tabelle (Cloud), Open-Source-Tabelle (HF-Links, Hosting, Praxis-Tests, Tester-Attribution), Hector's Active Stack, Post-Transformer-Outlook, DRACO-Fusion-Ergebnisse | 11 Wiki-Quellen + MEMORY.md | | [LLM Sycophancy, Confabulation & Session-Statelessness — The Nano Banana Incident](concepts/llm/llm-sycophancy-confabulation.md) | Drei Mechanismen die LLM-Aussagen über eigene Fähigkeiten untrustworthy machen: Session-Statelessness, Sycophantic Compliance, Confabulation. Lüge-vs-Confabulation-vs-Sycophancy-Distinktion. Anti-Pattern: Modul-Aktivierung per Chat. Fallbeispiel: Gemini erfindet "Nano Banana 2". Goldene Regel: Provider-Doku > Chat | other/2026-06-26_nanobana-incident-sycophancy-confabulation.md | | [ReDS — Resilient Decentralized Swarm](concepts/llm/reds-resilient-decentralized-swarm.md) | Brian Roemmele's Konzept für dezentrale KI-Entwicklung als Gegenmodell zu Amodei's Zentralismus. Resilient (zensur-resistent) + Decentralized (keine zentrale Kontrolle) + Swarm (koordinierte Akteure). Erweitert Cloud-Exit/Dezentrale-KI-These um politische/soziale Dimension | xpost/2026-06-28_roemmele-reds-decentralized-ai-vs-amodei.md | +| [Chinese Model Cost Routing — The 87% Cost-Cut Playbook](concepts/llm/chinese-model-cost-routing.md) | DeRonin's 30-day field report: 6 Western→Chinese model swaps, 87% cost reduction, 4% quality drop, revenue unchanged. Swap matrix (Opus→Kimi K2.7, GPT-5.5→Qwen 3.7 Max, Sonnet→GLM 5.2, GPT-mini→MiMo V2.5, GPT-Image→Wan 2.5, Sora→Kling 3.0). Validates Barbell Routing + Factory-for-Gods thesis. Cross-refs to model-router skill | xpost/2026-06-29_deronin-chinese-ai-stack-cost-savings.md | ### AGI | Seite | Beschreibung | Quellen | diff --git a/wiki/log.md b/wiki/log.md index 175bc6f..4eafa00 100644 --- a/wiki/log.md +++ b/wiki/log.md @@ -927,3 +927,15 @@ Bestehende `post-transformer-llm-architectures.md` bleibt als Vier-Säulen-Über - log: this entry **Hector-Hauptthese:** Das Berman-Video komplettiert das Hermes-Tutorial-Quartett Ende Juni 2026 (Jonas Keil Desktop-Review → Alex Finn v0.17.0 → Peter Yang Full Course → Berman 2-Min-Setup). Zusammen decken sie die volle Bandbreite ab: von Desktop-App über Feature-Deep-Dive über kompletten 45min-Kurs bis zum 2-Minuten-VPS-Quickstart. Die Hostinger-Sponsorship ist strategisch interessant: Hosting wird zum Klick-Produkt, Hermes positioniert sich als die "easy button"-Alternative zu OpenClaw's CLI-first-Ansatz. Die direkte OpenClaw-Vergleichung in einem Sponsored-Video unterstreicht die Konkurrenz-Narrative. **Subagent-Modell:** ollama/glm-5.2:cloud + +## [2026-06-29] Ingest | DeRonin — "My entire AI stack is now Chinese 🇨🇳" (87% Cost-Cut Field Report) +**Type:** ingest | **Scope:** raw/xpost, wiki/concepts/llm, wiki/index +**Source:** X-Post by @DeRonin_ (https://x.com/DeRonin_/status/2071561335234531578) — shared by Pit Weber in OME-Gruppe Topic "Tips & Tricks" (Topic 27), 2026-06-29 +**Trigger:** DeRonin dokumentiert einen vollständigen 6-Modell-Swap von Western frontier zu Chinese alternatives mit 30-Tage-Ergebnis: 87% Kostenreduktion, 4% Qualitätsverlust, Revenue unverändert. 2.5K+ likes, 130K+ views. Full Article mit Routing-Logic für 2026-06-30 angekündigt. +**Actions:** +- raw: `raw/xpost/2026-06-29_deronin-chinese-ai-stack-cost-savings.md` (created — 2.9 KB; Frontmatter mit type/source_url/author/date/posted_by/topic/tags, vollständige Swap-Matrix-Tabelle, 30-Day-Outcome, Engagement-Metriken, Relevance-to-Our-Setup mit Cross-Refs) +- wiki (NEU): `concepts/llm/chinese-model-cost-routing.md` (created — 8.5 KB; Umfassende Analyse-Seite mit 7 Sektionen: (1) Source-Übersicht mit 3 Quellen, (2) Swap-Matrix mit allen 6 Tasks + 30-Day-Outcome-Tabelle, (3) Barbell-Routing-Connection mit Phasen-Mapping + Hector-vs-DeRonin-Vergleichstabelle, (4) Factory-for-Gods-Connection mit TheProphet-These + empirischer Validierung, (5) Quality-Cost-Curve mit task-abhängigem Schwellwert, (6) Chinese Model Landscape mit In-Our-Stack-Marking, (7) Architecture Implications mit 5 konkreten Takeaways. Cross-Refs zu 8 Wiki-Seiten + model-router skill.) +- wiki: `index.md` (updated — Header auf "43. Update", neuer LLM-Eintrag unter Concepts/LLM Sektion) +- log: this entry +**Hector-Hauptthese:** DeRonin's Post ist das empirische Missing Link zwischen TheProphet's Makro-These ("Factory for Gods") und unserer Routing-Architektur. Während TheProphet die wirtschaftliche Logik erklärte und Miles Deutscher die Barbell-Strategie formalisierte, beweist DeRonin mit 30 Tagen Production-Daten: Der Swap ist nicht hypothetisch — er ist revenue-neutral. Die wichtigste Nuance: Der Qualitäts-Schwellwert ist task-abhängig. Bei Agent Loops (GLM 5.2, 3% Gap) ist es ein No-Brainer. Bei Code Gen (Qwen 3.7 Max, 18% Gap) funktioniert es nur, weil Code-Verifikation billiger ist als Code-Generierung. Das ist die "verification cost" als entscheidende Variable — ein Konzept das in unserer 5-Tier-Routing-Logik noch nicht explizit modelliert ist. DeRonin's unabhängige Wahl von GLM 5.2 für Agent Loops validiert unsere Default-Modell-Entscheidung. Sein Split (Kimi für Reasoning, GLM für Agent Loops) ist feingranularer als unser aktuelles Setup und könnte als Optimierungs-Input für den model-router skill dienen. +**Subagent-Modell:** ollama/glm-5.2:cloud