{"id":5545,"date":"2026-04-25T08:53:17","date_gmt":"2026-04-25T07:53:17","guid":{"rendered":"https:\/\/www.utilewebsites.nl\/het-openclaw-avontuur-hoe-ik-de-context-muur-doorbrak-met-deepseek-v4\/"},"modified":"2026-04-25T09:12:40","modified_gmt":"2026-04-25T08:12:40","slug":"het-openclaw-avontuur-hoe-ik-de-context-muur-doorbrak-met-deepseek-v4","status":"publish","type":"post","link":"https:\/\/www.utilewebsites.nl\/en\/het-openclaw-avontuur-hoe-ik-de-context-muur-doorbrak-met-deepseek-v4\/","title":{"rendered":"The OpenClaw Adventure: How I Broke Through the “Context Wall” with DeepSeek V4"},"content":{"rendered":"\n

In the world of AI development, there is a big difference between 'fun experiments' and 'productive harmony'. In my search for the ideal digital companion for a complex creative process \u2013 from long videos to audio and images \u2013 I embarked on an adventure with OpenClaw. An adventure that led me along the edges of the cloud, until I found the key with a new player: DeepSeek.<\/strong><\/p>\n\n\n\n

The Start: Harmony with Route-LLM<\/h2>\n\n\n\n

For everyone who wants to embark on the OpenClaw adventure, there is one piece of advice: start with Route-LLM<\/strong>. It worked perfectly for me for a long time. The beauty of this system (via Abacus AI) is its versatility; all top models are ready for you and the system switches automatically based on your query. It is the ideal \"entry-level harmony\" for a creative process in which you don't want to constantly tinker with the back end yourself.<\/p>\n\n\n\n

The Wall: Context and Costly Tokens<\/h2>\n\n\n\n

But those who build big run into big limits. My project \u2013 orchestrating a complete pipeline for long videos \u2013 requires my agent to have an enormous memory. OpenClaw must constantly send along large amounts of documentation and history.<\/p>\n\n\n\n

Here I ran into two major problems:<\/p>\n\n\n\n

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  1. The \"Forgetfulness\":<\/strong> The standard models fell short on context memory for the complex structures I was building.<\/li>\n\n\n\n
  2. The Token Bill:<\/strong> Because there was no caching<\/em>, I paid for the full set of instructions and documents again with every single query.<\/li>\n<\/ol>\n\n\n\n

    I tried Gemini<\/strong> via Google Studio. Although Gemini can cache fantastically, I noticed that Google's API blocks an agent workflow (like OpenClaw) fairly quickly. Something that never happened with Route-LLM, but there I was missing the much-needed efficiency.<\/p>\n\n\n\n

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    The Revolution: DeepSeek V4 (April 2026)<\/h2>\n\n\n\n

    Around April 25, 2026<\/strong>, something happened that caught the entire AI community off guard: the release of the latest DeepSeek model<\/strong>. A lot is claimed in the media, but in my world the rule is: the proof is in the numbers.<\/strong><\/p>\n\n\n\n

    The first results of my tests are spectacular:<\/p>\n\n\n\n