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Big on quality. Light on compute. Meet MAI‑Image‑2‑Efficient, our production model built for rapid iteration—delivering 4× the efficiency of MAI‑Image‑2. Learn more here:

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Microsoft AI

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16,586 просмотров • 2 месяцев назад •via X (Twitter)

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Most image stacks bet on one giant, closed model. We don’t. We route each image gen request on Syntax to the best open-source model/LoRA for the job. Quality rises, iteration speeds up, costs stay sane, and creators aren’t locked into one model’s quirks. The future is orchestration, not monoliths.
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Most image stacks bet on one giant, closed model. We don’t. We route each image gen request on Syntax to the best open-source model/LoRA for the job. Quality rises, iteration speeds up, costs stay sane, and creators aren’t locked into one model’s quirks. The future is orchestration, not monoliths.

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NVidia just released PiD: super resolution in pixel space directly from model latents 🔎 4X resolution for any generated image, FAST! 🏎️💨 FLUX.1, 2 and Z-Image (Qwen Image coming) of course, i built a demo: generate 4K images with Z-Image
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NVidia just released PiD: super resolution in pixel space directly from model latents 🔎 4X resolution for any generated image, FAST! 🏎️💨 FLUX.1, 2 and Z-Image (Qwen Image coming) of course, i built a demo: generate 4K images with Z-Image

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How to create this kind of video game interface animation with GPT Image 2 and Seedance 2 why is it possible now thanks to GPT Image 2? This model is really good in terms of details and design interface. Also, this model allows you to rework multiple times an image without damaging the quality let me share my workflow👇
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How to create this kind of video game interface animation with GPT Image 2 and Seedance 2 why is it possible now thanks to GPT Image 2? This model is really good in terms of details and design interface. Also, this model allows you to rework multiple times an image without damaging the quality let me share my workflow👇

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Lost in the wild, built by the storm. Created with GPT Image 2 + Seedance 2.0 on insMind
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🚨 Real-time image-to-image editing drops on fal! 🎨 10+ FPS for instant results for FLUX.2 Klein ✨ Low latency, production-ready 💰 Hand-tuned kernels for real-time execution 🎬 Image editing at interactive speeds
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🚨 Real-time image-to-image editing drops on fal! 🎨 10+ FPS for instant results for FLUX.2 Klein ✨ Low latency, production-ready 💰 Hand-tuned kernels for real-time execution 🎬 Image editing at interactive speeds

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Text-to-image diffusion transformer models learn to align text and image representations as a byproduct of their conditional denoising task. By taking the dot product between the text and image representations of a DiT model (like Flux 2), you can create rich saliency maps.
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Text-to-image diffusion transformer models learn to align text and image representations as a byproduct of their conditional denoising task. By taking the dot product between the text and image representations of a DiT model (like Flux 2), you can create rich saliency maps.

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I built a GPT 2 workflow that turns one image into 20 viral ads GPT image 2 is the most powerful image model out there And you can use it to scale your ads campaign with Arcads workflow Comment Arcads to get the workflow now
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I built a GPT 2 workflow that turns one image into 20 viral ads GPT image 2 is the most powerful image model out there And you can use it to scale your ads campaign with Arcads workflow Comment Arcads to get the workflow now

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GPT Image 2 is now on Renoise. 50% off, limited time. Repost + drop "Image 2" or what you'd create first 👇 4 winners get $20 Membership
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P-Image-Upscale is the fastest and cheapest image upscaler in the world: supporting outputs up to 128 MP under 1 seconds. A couple of weeks ago we released p-image-upscale, and it now works better than ever. It’s the fastest image upscaler in the world, supporting outputs up to 128 MP while keeping pricing simple and predictable: - $0.005/image for 1–4 MP - $0.01/image for 4–8 MP - $0.02/image for 8–16 MP - $0.04/image for 16–32 MP - $0.06/image for 32–64 MP - $0.12/image for 64–128 MP That means you can go from low-res input to production-ready output with extreme speed, while preserving detail and keeping costs easy to understand. Available on: - Pruna AI | - each::labs | - inference.sh | - Replicate | - Runware | - Segmind | - WaveSpeedAI | - Wiro | If you’re building workflows where image quality, price, latency, and scale all matter, p-image-upscale is built for you.
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P-Image-Upscale is the fastest and cheapest image upscaler in the world: supporting outputs up to 128 MP under 1 seconds. A couple of weeks ago we released p-image-upscale, and it now works better than ever. It’s the fastest image upscaler in the world, supporting outputs up to 128 MP while keeping pricing simple and predictable: - $0.005/image for 1–4 MP - $0.01/image for 4–8 MP - $0.02/image for 8–16 MP - $0.04/image for 16–32 MP - $0.06/image for 32–64 MP - $0.12/image for 64–128 MP That means you can go from low-res input to production-ready output with extreme speed, while preserving detail and keeping costs easy to understand. Available on: - Pruna AI | - each::labs | - inference.sh | - Replicate | - Runware | - Segmind | - WaveSpeedAI | - Wiro | If you’re building workflows where image quality, price, latency, and scale all matter, p-image-upscale is built for you.

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