{"id":2158,"date":"2026-04-26T05:23:15","date_gmt":"2026-04-26T05:23:15","guid":{"rendered":"https:\/\/ai-box.eu\/?p=2158"},"modified":"2026-04-26T15:00:11","modified_gmt":"2026-04-26T15:00:11","slug":"building-an-ai-generated-browser-game-with-qwen-3-6-a-creative-experiment","status":"publish","type":"post","link":"https:\/\/ai-box.eu\/en\/large-language-models-en\/building-an-ai-generated-browser-game-with-qwen-3-6-a-creative-experiment\/2158\/","title":{"rendered":"Building an AI &#8211; Generated Browser Game with Qwen 3.6 A Creative Experiment"},"content":{"rendered":"<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">I&#8217;ve been exploring the intersection of local AI inference and creative generation, and I wanted to push it beyond the usual text and image boundaries and let the latest Qwen 3.6 model do the job. So I decided to build a browser game entirely AI-generated using Qwen 3.6 and to guide it not too much. Let the model be creative and create a game for a target ground around the age of 8 years.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>Hardware &amp; Infrastructure:<\/strong><\/p>\n<ul class=\"[li_&amp;]:mb-0 [li_&amp;]:mt-1 [li_&amp;]:gap-1 [&amp;:not(:last-child)_ul]:pb-1 [&amp;:not(:last-child)_ol]:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3\">\n<li class=\"whitespace-normal break-words pl-2\"><strong>2x RTX A6000 GPUs<\/strong> for parallel inference and token generation<\/li>\n<li class=\"whitespace-normal break-words pl-2\"><strong>Ollama<\/strong> as the inference server (local LLM orchestration)<\/li>\n<li class=\"whitespace-normal break-words pl-2\"><strong>Qwen qwen3.6:35b-a3b-bf16<\/strong> as the generative model<\/li>\n<li><strong>Hermes-Agents<\/strong> as the Agent driving the development (very successfull)<\/li>\n<\/ul>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">This setup provides enough horsepower to run a large 35B parameter model efficiently while maintaining reasonable latency for interactive game development.<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/ai-box.eu\/en\/large-language-models-en\/building-an-ai-generated-browser-game-with-qwen-3-6-a-creative-experiment\/2158\/#The_Model_Qwen_36_35b-a3b-bf16\" >The Model: Qwen 3.6:35b-a3b-bf16<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/ai-box.eu\/en\/large-language-models-en\/building-an-ai-generated-browser-game-with-qwen-3-6-a-creative-experiment\/2158\/#The_Key_Learning_Let_the_Model_Breathe\" >The Key Learning: Let the Model Breathe<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/ai-box.eu\/en\/large-language-models-en\/building-an-ai-generated-browser-game-with-qwen-3-6-a-creative-experiment\/2158\/#Download\" >Download:<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/ai-box.eu\/en\/large-language-models-en\/building-an-ai-generated-browser-game-with-qwen-3-6-a-creative-experiment\/2158\/#The_Workflow\" >The Workflow<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/ai-box.eu\/en\/large-language-models-en\/building-an-ai-generated-browser-game-with-qwen-3-6-a-creative-experiment\/2158\/#The_Next_Frontier\" >The Next Frontier<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\"><span class=\"ez-toc-section\" id=\"The_Model_Qwen_36_35b-a3b-bf16\"><\/span>The Model: Qwen 3.6:35b-a3b-bf16<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The Qwen 3.6 model in its 35B quantized form (bf16) struck the right balance for this project:<\/p>\n<ul class=\"[li_&amp;]:mb-0 [li_&amp;]:mt-1 [li_&amp;]:gap-1 [&amp;:not(:last-child)_ul]:pb-1 [&amp;:not(:last-child)_ol]:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3\">\n<li class=\"whitespace-normal break-words pl-2\"><strong>Size<\/strong>: Large enough for coherent, creative output<\/li>\n<li class=\"whitespace-normal break-words pl-2\"><strong>Speed<\/strong>: Quantized to run efficiently on dual A6000s<\/li>\n<li class=\"whitespace-normal break-words pl-2\"><strong>Quality<\/strong>: Excellent instruction-following and creative generation<\/li>\n<\/ul>\n<div id=\"attachment_2161\" style=\"width: 1034px\" class=\"wp-caption alignnone\"><a href=\"https:\/\/ai-box.eu\/wp-content\/uploads\/2026\/04\/Jump_and_run_game.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-2161\" class=\"size-large wp-image-2161\" src=\"https:\/\/ai-box.eu\/wp-content\/uploads\/2026\/04\/Jump_and_run_game-1024x576.jpg\" alt=\"Hermes-Agent - Jump and run game\" width=\"1024\" height=\"576\" srcset=\"https:\/\/ai-box.eu\/wp-content\/uploads\/2026\/04\/Jump_and_run_game-1024x576.jpg 1024w, https:\/\/ai-box.eu\/wp-content\/uploads\/2026\/04\/Jump_and_run_game-300x169.jpg 300w, https:\/\/ai-box.eu\/wp-content\/uploads\/2026\/04\/Jump_and_run_game-768x432.jpg 768w, https:\/\/ai-box.eu\/wp-content\/uploads\/2026\/04\/Jump_and_run_game-1536x864.jpg 1536w, https:\/\/ai-box.eu\/wp-content\/uploads\/2026\/04\/Jump_and_run_game-2048x1152.jpg 2048w, https:\/\/ai-box.eu\/wp-content\/uploads\/2026\/04\/Jump_and_run_game-1080x608.jpg 1080w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><p id=\"caption-attachment-2161\" class=\"wp-caption-text\">Hermes-Agent &#8211; Jump and run game<\/p><\/div>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\"><span class=\"ez-toc-section\" id=\"The_Key_Learning_Let_the_Model_Breathe\"><\/span>The Key Learning: Let the Model Breathe<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">Here&#8217;s what I discovered through experimentation: <strong>Don&#8217;t over-guide the model. Let it be creative.<\/strong><\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">My initial approach was heavily constrained specific rules, exact game mechanics, rigid structures. The results were&#8230; predictable and flat.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The breakthrough came when I switched to <strong>open-ended prompting<\/strong>:<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">Instead of:<\/p>\n<blockquote class=\"ml-2 border-l-4 border-border-300\/10 pl-4 text-text-300\">\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">&#8220;Generate a game with these exact rules: 1) Move with arrow keys 2) Collect items 3) Avoid enemies&#8221;<\/p>\n<\/blockquote>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">I tried then:<\/p>\n<blockquote class=\"ml-2 border-l-4 border-border-300\/10 pl-4 text-text-300\">\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">&#8220;Design a fun, engaging browser game. Think about what would make it interesting and enjoyable for a 8 year old girl. What mechanics would be surprising? What visuals would pop?&#8221;<\/p>\n<\/blockquote>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The difference was striking. When I stepped back and let Qwen explore the design space, it generated more innovative game mechanics, unexpected twists, and creative solutions I hadn&#8217;t considered.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>The lesson<\/strong>: Large language models are powerful ideation partners. They don&#8217;t just follow instructions they can contribute creative vision. The trick is knowing when to be prescriptive and when to be permissive.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Download\"><\/span>Download:<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>If you like to download the small game and AGENT.md file Hermes-Agent generated then just klick the link: <a href=\"https:\/\/ai-box.eu\/wp-content\/uploads\/2026\/04\/Jump_and_run_game.zip\">Jump_and_run_game<\/a><\/p>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\"><span class=\"ez-toc-section\" id=\"The_Workflow\"><\/span>The Workflow<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ol class=\"[li_&amp;]:mb-0 [li_&amp;]:mt-1 [li_&amp;]:gap-1 [&amp;:not(:last-child)_ul]:pb-1 [&amp;:not(:last-child)_ol]:pb-1 list-decimal flex flex-col gap-1 pl-8 mb-3\">\n<li class=\"whitespace-normal break-words pl-2\"><strong>Prompt Engineering<\/strong> (local Ollama + Qwen): High-level game concept \u2192 Qwen generates HTML and CSS \/ JavaScript if you ask for.<\/li>\n<li class=\"whitespace-normal break-words pl-2\"><strong>Iteration<\/strong>: Review output, ask follow-up questions, refine (staying conversational, not mechanical)<\/li>\n<li class=\"whitespace-normal break-words pl-2\"><strong>Testing<\/strong>: Run game directly in browser, identify issues<\/li>\n<li class=\"whitespace-normal break-words pl-2\"><strong>Refinement Loop<\/strong>: Let the model fix bugs, enhance features, improve UX based on feedback<\/li>\n<\/ol>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The entire process happened locally by using the Hermes-Agent no cloud API calls, no rate limits, full privacy because I am using Ollama as inferencing server.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">This experiment raises some interesting questions I was thinking about after playing for a while:<\/p>\n<ul class=\"[li_&amp;]:mb-0 [li_&amp;]:mt-1 [li_&amp;]:gap-1 [&amp;:not(:last-child)_ul]:pb-1 [&amp;:not(:last-child)_ol]:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3\">\n<li class=\"whitespace-normal break-words pl-2\"><strong>Accessibility<\/strong>: If 35B models can run locally on accessible hardware (dual A6000s), what becomes possible for indie developers?<\/li>\n<li class=\"whitespace-normal break-words pl-2\"><strong>Iteration Speed<\/strong>: Traditional game development cycles vs. AI-assisted co-creation<\/li>\n<li class=\"whitespace-normal break-words pl-2\"><strong>Creativity<\/strong>: Does guided creativity produce better results than constrained design?<\/li>\n<li class=\"whitespace-normal break-words pl-2\"><strong>Scalability<\/strong>: What if tablets with integrated AI accelerators become the development platform?<\/li>\n<\/ul>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\"><span class=\"ez-toc-section\" id=\"The_Next_Frontier\"><\/span>The Next Frontier<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The infrastructure for AI-assisted game development is already here. The models are capable. The hardware is becoming more affordable. What&#8217;s emerging is a new creative workflow where humans and AI collaborate as true partners.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">This wasn&#8217;t about replacing game designers. It was about accelerating ideation and proving that local LLMs can handle complex, structured creative tasks and not just text or image generation.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>I&#8217;ve been exploring the intersection of local AI inference and creative generation, and I wanted to push it beyond the usual text and image boundaries and let the latest Qwen 3.6 model do the job. So I decided to build a browser game entirely AI-generated using Qwen 3.6 and to guide it not too much. [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":2161,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[162],"tags":[990,979,984,982,983,637,988,986,257,987,989,985,980,306,981,315],"class_list":["post-2158","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-large-language-models-en","tag-ai-agents","tag-ai-game-development","tag-ai-assisted-game-design","tag-browser-games","tag-childrens-games","tag-creative-ai","tag-creative-prompting","tag-game-development-workflow","tag-generative-ai-en","tag-hermes-agent","tag-indie-game-development","tag-local-ai-models","tag-local-llm-inference","tag-ollama-en","tag-qwen-3-6","tag-rtx-a6000-en","et-has-post-format-content","et_post_format-et-post-format-standard"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Building an AI - Generated Browser Game with Qwen 3.6 A Creative Experiment - Exploring the Future: Inside the AI Box<\/title>\n<meta name=\"description\" content=\"Discover how I built an AI-generated browser game using Qwen 3.6 and dual RTX A6000 GPUs with Ollama. 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