u/Boring_Aioli7916

Generational USA hatewatch incoming at least from me tbh. Politics always find a way to ruin things at the end. Trump and corrupt FIFA..? match made in heaven it seems. Lets go, devils 🇧🇪

Positively suprised.

Nisam ocekivao mnogo, ali ova serija me je potpuno oduvala u pozitivnom smislu. STAR CITY je spin-off For All Mankind, samo gledano iz sovjetskog ugla i iskreno, mnogo ali MNOGO mi je bolja serija za sad. FAM mi je uvek bio interesantan po konceptu, ali nesto mi je americka strana price bila predugacka i dosadna, ne znam sta tacno ali sve mi je bilo presporo i pomalo otrcano/vec vidjeno tu. Ovde je atmosfera gusca, tenzija realnija, a paranoja i birokratska nocna mora daju osecaj kao da gledate Chernobyl u svemiru. Ako volite sci-fi, ali i tamnu, klaustrofobicnu dramu u stilu Lives of Other onda je ovo je topla preporuka. Oh, da.. odabir glumaca i nivo glume u seriji je takodje za svaku pohvalu.

Full article and source: https://news.futunn.com/en/post/75068082/ubs-group-finds-60-have-already-started-curbing-ai-spending?level=1&data_ticket=1782494357196705

• Unusual Founder Control: Instead of ceding control, Liang personally invested roughly $3 billion (over RMB 20 billion) to maintain a massive equity stake and strict management control.
• Strict "No-Poaching" Rule: Liang reportedly enforced non-negotiable terms for his investors, fiercely protecting DeepSeek's staff from rival firms poaching them.
• Chinese AI lab DeepSeek raised over $7.4 billion in its debut external funding round, securing a valuation of over $50 billion. This milestone makes it China's most valuable artificial intelligence startup.

Sources: https://www.cnbc.com/2026/06/18/no-poaching-our-people-chinas-deepseek-reportedly-tells-investors.html

https://www.scmp.com/tech/big-tech/article/3357525/how-deepseeks-landmark-funding-secures-liang-wenfengs-grip-chinas-ai-rivalry-heats

https://www.techflowpost.com/article/32075

https://www.finsmes.com/2026/06/deepseek-raises-over-7-4-billion-in-maiden-funding-at-a-post-money-valuation-exceeding-50-billion.html

Amazing workhorse with its own moments of brilliance.. An all-arounder. I m sure in few years V4 flash will be remembered as hall of famer model just like R1 is.

How do you guy access it or set V4 pro via Cline? my current version of cline is 3.87.0

How are you guys bypassing this limitation?

Are people deploying local middleware proxies (like running a tiny Python script or a local LiteLLM server at localhost to catch Cline's traffic, inject the "reasoning" payload, and then forward it to OpenRouter)?

Are you guys shifting your deep-thinking workflows entirely to alternative extensions like Continue (which natively exposes an extraBodyProperties JSON config box)?

Or does DeepSeek's auto-scaler efficiently ramp up its own test-time compute anyway when Cline feeds it a massive multi-file context?

My Current Sidebar Setup:

• API Provider: OpenAI Compatible (or Native OpenRouter)
• Base URL: [https://openrouter.ai/api/v1](https://openrouter.ai/api/v1)
• Model ID: deepseek/deepseek-v4-pro
• The "Nerf" Prevention Fix: To stop Cline from truncating my context window under OpenAI Compatible, I use the Custom Model Info box to manually pin the true V4 Pro architecture bounds: JSON{ "contextWindow": 1048576, "maxTokens": 384000, "supportsImages": false }

​

Here is LLM analysis I did. 
---

### 🔍 The Deep-Dive Analysis & Why Common Advice Fails

When trying to inject the parameters for provider locking (`"allow_fallbacks": false`) and scaling compute (`"reasoning": {"effort": "xhigh"}`), I went down the rabbit hole of where Cline hides its configuration state. Here is what I uncovered:

#### 1. The `settings.json` Dead End
Many older guides suggest adding `cline.openAiCompatible.extraBody` blocks to your global VS Code `settings.json`. However, inspecting my system's raw file path (`AppData\Roaming\Code\User\settings.json`) reveals that modern vanilla Cline **does not expose its properties there**. Its `package.json` contains an empty properties schema. All active provider state is cached internally in VS Code's `globalState` relational database.

#### 2. The Model Suffix Hallucination (A Dangerous Trap)
I ran a diagnostic check with an LLM configuration scout script that inspected my internal `\.cline\data\globalState.json`. It suggested a clever-sounding fix: manually editing the file to append a suffix directly to the model configuration tags, turning them into `"actModeOpenRouterModelId": "deepseek/deepseek-v4-pro-xhigh"`. 

**Do not do this.** This is a complete hallucination. OpenRouter does not host separate split model strings based on suffix names. If you force this change inside your local state data, OpenRouter's routing layer will instantly spit back a `404: Model Not Found` error. 

#### 3. The Core Constraint: Strict Payload Stripping
OpenRouter handles DeepSeek's scaling mode and provider behaviors exclusively via custom JSON request body blocks:
```json
{
  "model": "deepseek/deepseek-v4-pro",
  "reasoning": { "effort": "xhigh" },
  "provider": { "allow_fallbacks": false, "order": ["deepseek"] }

A terminal AI coding agent designed specifically for DeepSeek API's prefix caching mechanism. It uses a cache-first architecture to keep token costs extremely low.

Reasonix is a DeepSeek-native terminal coding agent designed around prefix cache stability. In real-world testing, it processed 435 million input tokens in one day for only about $12, with a 99.82% cache hit rate. Four architectural pillars: cache-first conversation loop, R1 reasoning chain reuse, tool-call repair, and cost control. Built-in web search (Mojeek by default, switchable to SearXNG), MCP, hooks, skills, memory, persistent sessions, and a web dashboard. One-click launch with npx, MIT license, built with TypeScript.Intentionally supports only DeepSeek — no multi-model switching. Focused on extreme optimization for a single backend.

Link: https://github.com/esengine/deepseek-reasonix

Have you guys tried it yet?

Used Qwen 3.6 max yesterday for the first time for performing comperhensive audit of my project. I was blown away. Can only think what 3.7 series are capable of. I'm really impressed by Qwen team.