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Get the Agent OS 👉 https://www.skool.com/ai-profit-lab-7462/about Want to make money and save time with AI? Join here: https://www.skool.com/ai-profit-lab-7462/about Video notes + links to the tools 👉 https://www.skool.com/ai-profit-lab-7462/about Get a FREE AI Course + Community + 1,000 AI Agents 👉 https://www.skool.com/ai-seo-with-julian-goldie-1553/about Get a FREE AI SEO Strategy Session → https://go.juliangoldie.com/strategy-session?utm=julian Get 200+ Free AI SEO Prompts → https://go.juliangoldie.com/chat-gpt-prompts Get out SEO link building book here 👉 https://go.juliangoldie.com/opt-in?utm=julian Inkling Model Review: Open-Weights MoE with 1M Context (vs GLM 5.2) The video tests Inkling, a newly released open-weights Mixture of Experts model from Thinking Machines (975B total parameters, 41B active) with a 1M-token context window, pretrained on 45T tokens, available on Hugging Face, usable in OpenCode, and fine-tunable on Tinker via an API key and the Inkling playground. The host demonstrates outputs built in an “Ink Machine” workflow, showing strong visual one-shot webpage and design examples (some impressive, some poor), but highlights major weaknesses in 3D/physics-style game builds where projects break or feel uninteresting. On Goldy Bench (about 50 tasks), Inkling ranks 14th out of ~30 models with an average score of 6/10, outperforming some open models but not matching GLM 5.2, which performs much better in head-to-head game demos. The episode concludes by encouraging viewers to test models themselves and promotes the creator’s Agent OS and AI Profit Ballroom community. 00:00 Meet Inkling 00:19 Specs and Availability 01:20 Testing in OpenCode 01:56 Design Demos Showcase 02:38 Goldy Bench Results 03:46 Where It Falls Short 04:07 3D Game Failures 04:47 Landing Page Output 05:46 Inkling vs GLM 5.2 06:55 How to Use the API 07:26 Takeaways and Benchmarks 08:25 Agent OS and Community 09:24 Final Thanks