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Running AI image generation for thousands of users at once has 3 problems: cost, speed, and crashing servers. So we built a different way with and AkashML. One that brings image gen cost down to just 1 cent/image. Watch and read the full breakdown ⏬ Akash Network

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RazerAI

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66,038 просмотров • 3 месяцев назад •via X (Twitter)

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AI is moving fast. And OpenAI's new image model proves it — knowing how to use AI images to your advantage is now crucial for designers. So we teamed up with Nick St. Pierre (The AI Image Master) to walkthrough one of the best AI image generation tools right now, Midjourney, and build a full website using only AI images, in 1 hour. Watch the full breakdown👇
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AI is moving fast. And OpenAI's new image model proves it — knowing how to use AI images to your advantage is now crucial for designers. So we teamed up with Nick St. Pierre (The AI Image Master) to walkthrough one of the best AI image generation tools right now, Midjourney, and build a full website using only AI images, in 1 hour. Watch the full breakdown👇

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Game-Changer Alert! Introducing Neuro Image Gen – The ultimate AI image generator powered by Neurolov's decentralized GPU network, delivering ultra-realistic, high-resolution, and completely free image generation! ✨ No fees. No ads. No limits. Just pure AI magic. ✨ Experience DSLR-quality AI images instantly—fueled by the power of a next-gen decentralized GPU network for unmatched speed and precision! 🔗 [ Your Vision. Our AI. Let's Create Together.
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Game-Changer Alert! Introducing Neuro Image Gen – The ultimate AI image generator powered by Neurolov's decentralized GPU network, delivering ultra-realistic, high-resolution, and completely free image generation! ✨ No fees. No ads. No limits. Just pure AI magic. ✨ Experience DSLR-quality AI images instantly—fueled by the power of a next-gen decentralized GPU network for unmatched speed and precision! 🔗 [ Your Vision. Our AI. Let's Create Together.

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You can now use rendered frames for image-to-image and image-to-video AI Generation on The Render Network Simply click “Iterate with AI” and instantly create new image + video variations right from the Render job page. No downloads, no switching tabs - just click and create. Try at: Learn more:
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You can now use rendered frames for image-to-image and image-to-video AI Generation on The Render Network Simply click “Iterate with AI” and instantly create new image + video variations right from the Render job page. No downloads, no switching tabs - just click and create. Try at: Learn more:

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📸 Introducing Replicate Image Editing Arena. We heard you needed an easy way to compare all of the latest image editing models. Evaluate models like FLUX.2, Nano Banana, Seedream, Qwen Edit, and Reve for speed, cost, and performance...all in one interface.
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📸 Introducing Replicate Image Editing Arena. We heard you needed an easy way to compare all of the latest image editing models. Evaluate models like FLUX.2, Nano Banana, Seedream, Qwen Edit, and Reve for speed, cost, and performance...all in one interface.

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45,689 просмотров • 9 месяцев назад

Claude Fable 5 has been out for a day. I already one-shotted a voxel spaceship racer with it. I fed it a reference image of a track layout and told it to build a full game around that shape. Missiles, boost zones, 3 AI opponents, 3 laps, a HUD with speed and health. Fable 5 read the image, traced the track geometry, and built the entire thing. One prompt. This is what Mythos-class models do to the build cycle.
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Claude Fable 5 has been out for a day. I already one-shotted a voxel spaceship racer with it. I fed it a reference image of a track layout and told it to build a full game around that shape. Missiles, boost zones, 3 AI opponents, 3 laps, a HUD with speed and health. Fable 5 read the image, traced the track geometry, and built the entire thing. One prompt. This is what Mythos-class models do to the build cycle.

God of Prompt

27,386 просмотров • 2 месяцев назад

most AI APIs either cost too much or lock the best models behind expensive plans. then i came across Agnes AI. it’s one of the few platforms giving developers access to text, image, and video AI models through a single API. their ecosystem gives you direct access to top-tier models like - Agnes-2.0-Flash for text - Agnes-Image-2.0 for image - Agnes-Video-V2.0 for video Instead of managing different providers for different tasks, everything works from one place. what stood out to me: > one API for text, image, and video generation > OpenAI-compatible API, so integration is straightforward > built for speed and scalability > free access for developers to start building > useful for everything from chatbots to image generation and content automation if you’re building AI products, it’s worth taking a look while it’s still flying under the radar. sometimes the biggest advantage is finding great tools before everyone else does. check out Agnes AI here, get free access for developers : and if you’re building with it, join the developer community here: Agnes AI #AgnesAI #AgnesAPI #BuildWithAgnes #MultimodalAI #AIforDevs #DeveloperAPI #AIParity
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most AI APIs either cost too much or lock the best models behind expensive plans. then i came across Agnes AI. it’s one of the few platforms giving developers access to text, image, and video AI models through a single API. their ecosystem gives you direct access to top-tier models like - Agnes-2.0-Flash for text - Agnes-Image-2.0 for image - Agnes-Video-V2.0 for video Instead of managing different providers for different tasks, everything works from one place. what stood out to me: > one API for text, image, and video generation > OpenAI-compatible API, so integration is straightforward > built for speed and scalability > free access for developers to start building > useful for everything from chatbots to image generation and content automation if you’re building AI products, it’s worth taking a look while it’s still flying under the radar. sometimes the biggest advantage is finding great tools before everyone else does. check out Agnes AI here, get free access for developers : and if you’re building with it, join the developer community here: Agnes AI #AgnesAI #AgnesAPI #BuildWithAgnes #MultimodalAI #AIforDevs #DeveloperAPI #AIParity

MIKE

14,591 просмотров • 1 месяц назад

The biggest downside to Nano Banana Pro is the cost ($0.25/image) and slow generation speed. Here's a workflow that addresses both: 1 prompt = 9 distinct images at 1K resolution (~3 cents per image) The key is prompting each grid position individually, so you can test different lighting, backgrounds, or angles simultaneously. Iterate on different looks quickly and pick your winner. The workflow: → Extracts all 9 images → You select your favorite → Upscales it to 4K while referencing your input image to maintain consistency + details
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The biggest downside to Nano Banana Pro is the cost ($0.25/image) and slow generation speed. Here's a workflow that addresses both: 1 prompt = 9 distinct images at 1K resolution (~3 cents per image) The key is prompting each grid position individually, so you can test different lighting, backgrounds, or angles simultaneously. Iterate on different looks quickly and pick your winner. The workflow: → Extracts all 9 images → You select your favorite → Upscales it to 4K while referencing your input image to maintain consistency + details

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107,395 просмотров • 8 месяцев назад

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introducing nano banana 2 lite: our fastest, most cost-effective gemini image model yet built for high-velocity developer pipelines, it delivers text-to-image outputs in 4 seconds at just $0.034 per 1K-resolution image swap it into your workflow today via ai studio and the gemini api

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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 shell | - Replicate | - Runware | - Segmind | - WaveSpeedAI | - Wiro AI — Ship AI Faster | 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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11,343 просмотров • 1 год назад

New course: Efficient Inference with SGLang: Text and Image Generation, built in partnership with LMSys LMSYS Org and RadixArk RadixArk, and taught by Richard Chen Richard Chen, a Member of Technical Staff at RadixArk. Running LLMs in production is expensive, and much of that cost comes from redundant computation. This short course teaches you to eliminate that waste using SGLang, an open-source inference framework that caches computation already done and reuses it across future requests. When ten users share the same system prompt, SGLang processes it once, not ten times. The speedups compound quickly, especially when there's a lot of shared context across requests. Skills you'll gain: - Implement a KV cache from scratch to eliminate redundant computation within a single request - Scale caching across users and requests with RadixAttention, so shared context is only processed once - Accelerate image generation with diffusion models using SGLang's caching and multi-GPU parallelism Join and learn to make LLM inference faster and more cost-efficient at scale!
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New course: Efficient Inference with SGLang: Text and Image Generation, built in partnership with LMSys LMSYS Org and RadixArk RadixArk, and taught by Richard Chen Richard Chen, a Member of Technical Staff at RadixArk. Running LLMs in production is expensive, and much of that cost comes from redundant computation. This short course teaches you to eliminate that waste using SGLang, an open-source inference framework that caches computation already done and reuses it across future requests. When ten users share the same system prompt, SGLang processes it once, not ten times. The speedups compound quickly, especially when there's a lot of shared context across requests. Skills you'll gain: - Implement a KV cache from scratch to eliminate redundant computation within a single request - Scale caching across users and requests with RadixAttention, so shared context is only processed once - Accelerate image generation with diffusion models using SGLang's caching and multi-GPU parallelism Join and learn to make LLM inference faster and more cost-efficient at scale!

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1/4 🚀We are launching Qwen-Image-2.0, a next-generation foundational image generation model. The key highlights of Qwen-Image-2.0 include: Professional Typography Rendering: Supports 1k-token instructions for direct generation of professional infographics, including PPTs, posters, comics, and more. Stronger Semantic Adherence: Native 2K resolution support for finely detailed realistic scenes, including people, nature, and architecture. Improved Text Rendering: Integrated understanding and generation capabilities, unifying image generation and editing in a single mode Lighter Model Architecture: Smaller model size with faster inference speed.

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Found a way to make nano-banana-pro insanely cost-effective on fal I built a workflow that generates 9 4K images for a total of $0.21. That’s just $0.023 per image. That is a ~92% cost reduction. The key is grid generation. I added a 'Crop Node' as a workflow utility specifically for this. It takes the grid output, splits it, and then we upscale everything using SeedVR

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TurboEdit Instant text-based image editing discuss: We address the challenges of precise image inversion and disentangled image editing in the context of few-step diffusion models. We introduce an encoder based iterative inversion technique. The inversion network is conditioned on the input image and the reconstructed image from the previous step, allowing for correction of the next reconstruction towards the input image. We demonstrate that disentangled controls can be easily achieved in the few-step diffusion model by conditioning on an (automatically generated) detailed text prompt. To manipulate the inverted image, we freeze the noise maps and modify one attribute in the text prompt (either manually or via instruction based editing driven by an LLM), resulting in the generation of a new image similar to the input image with only one attribute changed. It can further control the editing strength and accept instructive text prompt. Our approach facilitates realistic text-guided image edits in real-time, requiring only 8 number of functional evaluations (NFEs) in inversion (one-time cost) and 4 NFEs per edit. Our method is not only fast, but also significantly outperforms state-of-the-art multi-step diffusion editing techniques.
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Go from weeks of visual effects work to instant visualization with Gen-4.5 Image to Video. Just drop an image in and ask for what you want. Looking for more tips? Check out our full collection of tutorial and guides at the link below.

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Filmmaker Öner S. Biberkökü shares his "screenshot strategy" for building a full narrative from a single starting point during this In the Flow interview. Thanks Oner for the partnership! "At the end of the shot, you can take a screenshot, give it again [to Flow], and you now have a new image of that character in a different situation... So I think, with one image, you can stay in the flow, and make a story." Watch his breakdown:

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Week two of optimizing my "image to CAD" web app with fable 5 and threeJS. Now with more logic and detail. Still some bugs and potential to optimize. One shot cost around 8$ for this LOD. But I think image to threeJS have so mutch potential. What you say?

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We have released an update for both text to video and image to video generation with Gen-2, bringing major improvements to both the fidelity and consistency of video results. Try it now at

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