Uploaded August 2026 | Updated September 2026, 2 weeks ago
🚀 The LangChain 10 Days FREE Bootcamp is live: 10 lessons, free AI models only, from your first API call to a production grade RAG agent. Start with Day 0 for the roadmap and setup.
📺 Full playlist: youtube.com/watch?v=KJ3_NExk7-Q&list=PLW4pPr9JCovI&index=1
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Qwen 3.8 vs Muse Glimmer vs Gemma 4: I ran all three local models on Ollama and had Claude Code build the same HTML canvas games with each, so you can see which one actually writes better code on your own machine.
This is a hands-on, side-by-side coding test. Same prompt, three local models, three games each (Space Invaders, Breakout, and Tetris), all generated with Claude Code pointed at Ollama and running fully offline on an RTX 5090. If you just want to see how Qwen 3.8 27B, Meta's Muse Glimmer, and Gemma 4 compare on real code generation, this video is complete on its own. The local Claude Code plus Ollama setup is a separate video, so tell me in the comments if you want that next.
📺 Full playlist (Local LLM Tutorial): youtube.com/playlist?list=PLc2rvfiptPSReropGbvDFpB6dneNBwqhD
⏱ Chapters:
0:00 Intro: Qwen 3.8 vs Muse Glimmer vs Gemma 4
0:23 Breakout: side-by-side comparison
1:37 How the games were built with Claude Code on Ollama
2:44 The benchmark prompt (Space Invaders, Breakout, Tetris)
4:01 Space Invaders comparison
5:24 Tetris comparison
6:09 Verdict: which model wins on code and UI
🔗 Resources:
Qwen 3.8 27B on Ollama: ollama.com/library/qwen3.8:27b
Benchmark prompts (GitHub): github.com/laxmimerit/llm-models-benchmarking-prompt
Qwen 3.8 27B vs Nemotron 3.5 vs Muse Glimmer on an RTX 5090
kgptalkie.com/tutorials/generative-ai/qwen-3-8-27b-vs-nemotron-3-5-vs-muse-glimmer
📺 Watch next:
Qwen 3.6 on Ollama, build games in one HTML file: youtube.com/watch?v=pQ-r6iCGpfw
🎓 Go deeper with my Udemy course:
Master LangChain v1 and Ollama, Chatbot, RAG and AI Agents: kgptalkie.com/langchain
If this comparison helped, hit like so more people find it, comment which local model you're running for coding, and subscribe with the bell so you don't miss the next test.
#Qwen3 #LocalLLM #Ollama #Gemma4 #ClaudeCode
🚀 The LangChain 10 Days FREE Bootcamp is live: 10 lessons, free AI models only, from your first API call to a production grade RAG agent. Start with Day 0 for the roadmap and setup.
📺 Full playlist: youtube.com/watch?v=KJ3_NExk7-Q&list=PLW4pPr9JCovI&index=1
----------
Qwen 3.8 vs Muse Glimmer vs Gemma 4: I ran all three local models on Ollama and had Claude Code build the same HTML canvas games with each, so you can see which one actually writes better code on your own machine.
This is a hands-on, side-by-side coding test. Same prompt, three local models, three games each (Space Invaders, Breakout, and Tetris), all generated with Claude Code pointed at Ollama and running fully offline on an RTX 5090. If you just want to see how Qwen 3.8 27B, Meta's Muse Glimmer, and Gemma 4 compare on real code generation, this video is complete on its own. The local Claude Code plus Ollama setup is a separate video, so tell me in the comments if you want that next.
📺 Full playlist (Local LLM Tutorial): youtube.com/playlist?list=PLc2rvfiptPSReropGbvDFpB6dneNBwqhD
⏱ Chapters:
0:00 Intro: Qwen 3.8 vs Muse Glimmer vs Gemma 4
0:23 Breakout: side-by-side comparison
1:37 How the games were built with Claude Code on Ollama
2:44 The benchmark prompt (Space Invaders, Breakout, Tetris)
4:01 Space Invaders comparison
5:24 Tetris comparison
6:09 Verdict: which model wins on code and UI
🔗 Resources:
Qwen 3.8 27B on Ollama: ollama.com/library/qwen3.8:27b
Benchmark prompts (GitHub): github.com/laxmimerit/llm-models-benchmarking-prompt
Qwen 3.8 27B vs Nemotron 3.5 vs Muse Glimmer on an RTX 5090
kgptalkie.com/tutorials/generative-ai/qwen-3-8-27b-vs-nemotron-3-5-vs-muse-glimmer
📺 Watch next:
Qwen 3.6 on Ollama, build games in one HTML file: youtube.com/watch?v=pQ-r6iCGpfw
🎓 Go deeper with my Udemy course:
Master LangChain v1 and Ollama, Chatbot, RAG and AI Agents: kgptalkie.com/langchain
If this comparison helped, hit like so more people find it, comment which local model you're running for coding, and subscribe with the bell so you don't miss the next test.
#Qwen3 #LocalLLM #Ollama #Gemma4 #ClaudeCode
