Image created with gemini-3.1-flash-image-preview with claude-opus-4.7. Image prompt: Using the provided reference image, keep the pure white landscape field, vertical type hierarchy, and galaxy-punchout Milky Way letterforms exactly as shown, but replace ‘HEROES’ with ‘IMAGES’ in the same bold condensed grotesque all-caps, replace ‘ALESSO’ with ‘SEEING TRULY’ in the same light geometric all-caps, and replace ‘TOVE LO’ with ‘DIFFUSION’ in the same condensed grotesque all-caps, while keeping ‘(we could be)’ and ‘FEATURING.’ unchanged. Maintain identical tracking, weights, font contrast, and the high-contrast starfield clipping inside every letter.
ChatGPT Images 2.0 – YouTube
I have been using GPT ImageGen-2 for the past weeks I didn’t think that better image-generators would be a big deal but it turns out that there is a quality threshold I didn’t expect, where you can now get text, slides, academic papers Look at what it does with my “”otter test””!
https://x.com/emollick/status/2046665274535854146
No bad ideas when you’re playing with ChatGPT Images 2.0 → Smarter visuals → Better editing and aesthetics Rolling out in Figma and Figma Weave
https://x.com/figma/status/2046673364496875977
Aspect Ratios & Resolution with ChatGPT Images 2.0 – YouTube
ChatGPT Images — Chameleon – YouTube
Instruction Following with ChatGPT Images 2.0 – YouTube
Multilingual & Text Rendering with ChatGPT Images 2.0 – YouTube
Slides & Infographics with ChatGPT Images 2.0 – YouTube
Thinking & Intelligence with ChatGPT Images 2.0 – YouTube
This is ChatGPT Images 2.0 – YouTube
GPT-5.5, not fully saturating the TikZ unicorn test yet but getting awfully close … (yes this is actual TikZ code, I personally find it so unbelievable that I’m putting the code below for anyone to verify for themself)
https://x.com/sebastienbubeck/status/2047383628922167390?s=46
GPT-ImageGen-2 did this in one shot, with just the prompt “”turn all of Tennyson’s Ulysses into a comic, across as many pages as needed. make it great, include the full text”” 10 pages, though it did use what seems to be the ImageGen-2 ‘s preferred “”spackled drawing”” style 1/
https://x.com/emollick/status/2046843402021380556
Nearly perfect (if unnerving). This is first shot, and the only real issue is the double hour hand.
https://x.com/emollick/status/2046761955642196381
Introducing OlmoEarth embeddings: Custom embedding exports from OlmoEarth Studio for downstream analysis | Ai2
https://allenai.org/blog/olmoearth-embeddings
ChatGPT Images 2.0 is a big leap forward in image generation intelligence. It’s much better at following detailed instructions, rendering dense text, understanding the world more accurately, and creating visuals that are more useful. And when you give it additional time to
https://x.com/nickaturley/status/2046677986242363731
GPT Image 2 + Codex: or how to make Codex not suck at UI. Step 1: Generate a UI image (native in Codex) Step 2: Get Codex to implement the UI based on it Step 3: Get Codex to iterate until it aligns with the image as much as possible Codex is bad at initial UI, but very good at
https://x.com/petergostev/status/2046720618566242657
Here is a manga made by ChatGPT Images 2.0 of @gabeeegoooh and me looking for more GPUs:
https://x.com/sama/status/2046672912833458597
My most popular AI post was a bunch of made-up “”graphs”” four years ago. Now, the new GPT-2 image generator does it for real (though not perfect) Here’s the famous AI task horizons graph with a touch of Basquiat, haunted by ghosts, from the Voynich manuscript, as a decaying pier.
https://x.com/emollick/status/2046728271849550331
Exciting news – GPT-Image-2 by @OpenAI has claimed the #1 spot across all Image Arena leaderboards! A clean sweep with a record-breaking +242 point lead in Text-to-Image – the largest gap we’ve seen to date. – #1 Text-to-Image (1512), +242 over #2 (Nano-banana-2 with web-search
https://x.com/arena/status/2046670703311884548
GPT Image Generation Models Prompting Guide
https://developers.openai.com/cookbook/examples/multimodal/image-gen-models-prompting-guide
Introducing ChatGPT Images 2.0 | OpenAI
https://openai.com/index/introducing-chatgpt-images-2-0/
Introducing ChatGPT Images 2.0 A state-of-the-art image model that can take on complex visual tasks and produce precise, immediately usable visuals, with sharper editing, richer layouts, and thinking-level intelligence. Video made with ChatGPT Images
https://x.com/OpenAI/status/2046670977145372771
Arena Trends: Text-to-Image, Jan 2026 – Apr 2026 For most of the year, @GoogleDeepMind and @OpenAI traded the top spot within a tight margin – GPT-Image vs. Nano Banana – with the rest of the field clustered below 1,200. Today, GPT-Image-2 breaks away with a score of 1,512, 242
https://x.com/arena/status/2046690103515648061
This wasn’t the case with previous image generators, but the LLM you select has a huge effect on GPT-imagegen-2 output. GPT-5.4 Thinking and GPT-5.4 Pro will produce much better images, especially for complex things. This is, of course, not intuitive or explained anywhere.
https://x.com/emollick/status/2046960756608868533
Access GPT Image 2.0 natively in Hermes Agent Update now to get access – just run `hermes update` and select your image generation tool model with `hermes tools`
https://x.com/NousResearch/status/2046693872773062834
✨ We’re excited to share that gpt-image-2 will be coming shortly to Canva AI 2.0! From highly-detailed generations to its creative intelligence, we can’t wait to see what you create. And with Magic Layers, you can edit everything like a design 🎨
https://x.com/canva/status/2046665346161988062
Playing with GPT Image 2 and really noticing the upgrade in fine detail + overall cohesion. Everything just feels like it belongs together a bit more ☀️ textures, lighting, composition all click. Try the model now in Firefly! Check the comments for the prompt 👇
https://x.com/AdobeFirefly/status/2046675148065923103
Same prompts as before, but now in GPT image-generator 2, page excerpts from: “”Eldritch Horrors as Pets: A Guide”” “”How Womblenauts Work”” “”Photographs of the People of New York Who Look Like Birds”” “”Cakes shaped like fish shaped like cakes”” Lots of great little lines in there
https://x.com/emollick/status/2046678198826479667
FlashLips: 100-FPS Mask-Free Latent Lip-Sync
https://azinonos.github.io/FlashLips/
A Scene is Worth a Thousand Features: Feed-Forward Camera Localization from a Collection of Image Features”” TL;DR: feed-forward localization builds a lightweight feature map and estimates camera pose in one pass, achieving fast and accurate relocalization across large scenes
https://x.com/Almorgand/status/2045194191081251178
Z-Image experiment. I expanded the patch-2 layers to patch-4. New layers = patch-2 layers averaged over sub-patches (in) / replicated (out), so the weights are already close with zero training. Finetuning now to clean it up. If it works: 2× image size at the same compute.
https://x.com/ostrisai/status/2045677110413668743
Image models tend to get much more stuck on a particular direction than text models, requiring clearing the context window fairly often. PerfectSquashBench is my new measure of how image models anchor. The squash remains merely fine after many attempts.
https://x.com/emollick/status/2047073009312121000
What you need to know about the Deep Research and Deep Research Max Update: – Can consults over 100 sources in one research task. – Generates native charts and infographics inline. – Accepts PDFs, CSVs, images, audio, and video inputs. – Max version uses ~160 search queries per
https://x.com/_philschmid/status/2046627179551944753
Meta just released Sapiens2 on Hugging Face High-resolution vision transformers pretrained on 1 billion human images, for human-centric perception: pose, segmentation, normals, and pointmaps.
https://x.com/HuggingPapers/status/2047410529010844044
new image model coming with some real magic within, to unlock new use cases in productivity and creativity livestream noon today
https://x.com/gdb/status/2046632580527554572
MIT engineers built an AI wristband that controls robots by reading your hand muscles. It works by using an ultrasound to capture images of the muscles and tendons in your wrist. An AI algorithm then translates those images into the exact position of all 5 fingers, tracking 22
https://x.com/rowancheung/status/2045158931367072104
Yay, finally! Introducing Vision Banana🍌 from @GoogleDeepMind, our unified model that outperforms SoTA specialist models on various vision tasks! By treating 2D/3D vision tasks as image generation, we unlock a new foundation for CV. Project page:
https://t.co/GQgRi6mWwC (1/5)
https://x.com/songyoupeng/status/2047312019976785944
🚨 GPT Image 2 is live on fal, day 0! 🔤 Strong text rendering 🧭 Better layout + UI adherence 🛠️ Cleaner preserve-and-change edits 📷 Strong everyday photoreal output
https://x.com/fal/status/2046667081068761527
people are speculating GPT-Image-2 is testing on @arena. the early examples being posted are pretty mind-boggling. all three of these images are AI generated. h/t @sawlygg @synthwavedd
https://x.com/blakeir/status/2040250530375606401?s=12
Though the images are very good, ChatGPT Image 2.0 does have the typical imagegen problem, which is that editing can be “”stubborn””, and attempts to get the AI to change details work well for the first round or two, but then progress slows. Putting the image in a new chat helps.
https://x.com/emollick/status/2046672707517886500
Leave a Reply