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Eleftheria Batsou

@BatsouElef • 55,995 subscribers

💼 Developer Advocate @zeropsio, @uptimerobot 🎤International MC/host 📩I help businesses & individuals to grow on X. DM me 💻Meetup Organizer | Public Speaker

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I spent the morning running cost projections for live interactive video, and the math on conventional models is completely broken for production. That is why Vivix.AI's W1 model caught my attention. At $0.003/sec, I can trigger nearly 77 equal-length W1 generations for the API cost of a single Seedance 2.5 call. When you build applications where video generates non-stop as users interact, unit economics dictate whether your project survives. This affordability is what makes W1’s identity as a real-time interactive video model practically usable. API access is active today, though browser playground tools are currently offline generation only while real-time updates roll out. Looking at their 4-way comparison with Seedance 2.5, Kling 3.0, and H3 Max fal featuring the slow-motion sneeze window shatter, W1 holds its visual fidelity remarkably well. You still see minor physical artifacts in high-density glass debris while full-scale model training progresses, but solving the real-time inference cost curve is the exact infrastructure breakthrough I was waiting for. The numbers that put W1 on my production shortlist 👇

I spent the morning running cost projections for live interactive video, and the math on conventional models is completely broken for production. That is why Vivix.AI's W1 model caught my attention. At $0.003/sec, I can trigger nearly 77 equal-length W1 generations for the API cost of a single Seedance 2.5 call. When you build applications where video generates non-stop as users interact, unit economics dictate whether your project survives. This affordability is what makes W1’s identity as a real-time interactive video model practically usable. API access is active today, though browser playground tools are currently offline generation only while real-time updates roll out. Looking at their 4-way comparison with Seedance 2.5, Kling 3.0, and H3 Max fal featuring the slow-motion sneeze window shatter, W1 holds its visual fidelity remarkably well. You still see minor physical artifacts in high-density glass debris while full-scale model training progresses, but solving the real-time inference cost curve is the exact infrastructure breakthrough I was waiting for. The numbers that put W1 on my production shortlist 👇

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I want to giveaway for free laptop #stickers. Would you be interested or nah?

I want to giveaway for free laptop #stickers. Would you be interested or nah?

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