Inference speed and hardware optimization
KV caching, step reduction, compilation, FP8, edge deployment, Apple Neural Accelerator, VRAM efficiency, and performance fixes.
25.9%
Best tweets about Flux AI
27 Best Tweets About Flux AI (2026)
Discover the best tweets about Flux AI, covering Black Forest Labs image models, prompts, fine-tuning, LoRAs, releases, benchmarks, and visual workflows.
Black Forest Labs FLUX image models, prompting, fine-tuning, LoRAs, releases, benchmarks, integrations, and demonstrated visual results.
- Creators
- 22
- Updated
Original Xholic analysis
What 27 top Flux AI posts reveal
The set frequently covers FLUX inference optimization, integrations and local deployment, fine-tuning or LoRA workflows, and model releases. It also includes demonstrations of interactive interfaces, visual outputs, and FLUX.1-based 3D-world pipelines.
- Dominant tone
- Positive
- Median score
- 28.5
- Leading format
- Announcement
- Recent posts
- 14.8%
77.8% of posts
All-time engagement
51.9% of posts
Published in 90 days
Conversation map
The themes creators return to
Integrations and local deployment
FLUX support in Diffusers, Spaces, Ollama, Draw Things, Open WebUI, Theta EdgeCloud, and local or terminal-based generation.
25.9%
Fine-tuning, LoRAs, and conditional control
LoRA training and hot-swapping, ControlNet tutorials, view-repair adapters, virtual try-on, and experimental model training.
22.2%
FLUX model releases and variants
New FLUX.2 Klein, FLUX.1 Schnell, Flux 2 Dev Turbo, Flux 3, and KV-cache-optimized model announcements.
18.5%
Prompted visual results and creative demos
Demonstrated image and video-like outputs, including historical footage, horror trailers, cinematic prompts, and editing quality.
14.8%
Model comparisons and competitive positioning
Comparisons with Midjourney, Nano Banana, and other image models, including quality, API, cost, style, and workflow tradeoffs.
11.1%
Real-time and interactive visual workflows
Live img2img, hand- and tracking-driven transformations, rapid visual ideation, and generative creative interfaces.
11.1%
FLUX-powered 3D scene generation
WorldGen pipelines that use FLUX.1 panoramas to create explorable Gaussian-splat or mesh-based 3D worlds.
7.4%
Tone and stance
Sentiment Positive leads
Author posture Supportive leads
Performance benchmark
- Median likes
- 99
- Median reposts
- 7
- Median replies
- 6
- Median views
- 8.4K
Posts with media make up 92.6% of this collection. Their median all-time score is 28.5, compared with 39.1 for text-only posts.
Format mix
- Announcement 51.9% · score 57.6
- Case Study 37% · score 24.8
- List 3.7% · score 4.69
- Opinion 3.7% · score 1.01
Consensus and debate
Where creators agree, and where they do not
Shared view
Inference optimization is a recurring topic
Posts describe KV-cache optimization for FLUX.2 Klein 9B, reduced-step calibration for FLUX, deployment on consumer-GPU edge nodes, and compile/FP8 optimization work for Flux.1.
Shared view
Customization workflows span several methods
The evidence includes a ControlNet-training tutorial, a LoRA intended to repair 3D views, a virtual try-on workflow using one LoRA, and work on hot-swapping LoRAs in compiled models.
Shared view
FLUX.1 appears in 3D-world pipelines
Two WorldGen posts describe FLUX.1 as the panorama-generation stage in pipelines that produce navigable Gaussian-splat or mesh-based scenes from prompts or images.
Shared view
Interactive visual workflows are demonstrated
Creators show FLUX.2 Klein in live img2img, hand-tracking-driven transformations, and a fast web demo for exploring visual ideas.
Open debate
Competitive positioning varies by task
One post characterizes Flux Klein 9B as faster and cheaper than Nano Banana 2.5 via API, with a wider style range than Nano Banana 2.5 but less range than Midjourney. Another lists FLUX.2 Pro as suited to developers building custom image applications, APIs, and automated workflows.
Open debate
A broad superiority claim is not corroborated by the comparison posts
One opinion post says Flux 2 Dev Turbo removed closed-source advantages. The comparison posts instead assign different models to different use cases, including Midjourney for aesthetic experimentation and FLUX variants for API or developer workflows.
What performs
Patterns behind standout posts
WorldGen posts are score outliers
The supplied outlier list includes the two WorldGen posts: 2039997609163833650 scored 483.24 and 2042140688503206183 scored 135.04.
Optimization and LoRA posts also appear among outliers
The supplied outlier list includes the FLUX.2 Klein 9B-KV post at 232.89 and the 3D-view-repair LoRA post at 232.38.
Media posts had a lower median score than text posts
Media appeared in 25 of 27 posts (92.6%). The supplied media median all-time score was 28.495, compared with 39.12 for text posts. Visual examples in the set include a historical-footage demo and an AI-horror trailer.
Announcements had a higher median than the overall set
Announcements were the largest format at 14 posts (51.9%), with a supplied median all-time score of 57.62, versus 28.495 for the overall set. The cited examples include WorldGen and FLUX.2 Klein 9B-KV announcements.
Statistical standouts
- View standout post 1 Score 483.2 · 16.96× median
- View standout post 2 Score 334.1 · 11.72× median
- View standout post 3 Score 232.9 · 8.17× median
- View standout post 4 Score 232.4 · 8.16× median
- View standout post 5 Score 135.0 · 4.74× median
Creator landscape
Who shapes this conversation
The five most represented creators account for 37% of the selected posts.
-
1. Cyril Diagne
@cyrildiagne
2 posts
-
2. Ostris
@ostrisai
2 posts
-
3. Hugues Bruyère
@smallfly
2 posts
-
4. Justine Moore
@venturetwins
2 posts
-
5. Wildminder
@wildmindai
2 posts
-
6. Jainam Parmar
@aiwithjainam
1 post
The set has a broad creator base with several repeat contributors
The set contains 22 creators. Cyril Diagne, Ostris, Hugues Bruyère, and Justine Moore each contributed two posts according to the creator analysis.
The sole tutorial entry exceeded the overall median
The only tutorial-format post is Ostris's ControlNet-training tutorial. Its supplied median all-time score is 95.458, above the overall median of 28.495.
Output-led demonstrations include a major score outlier
Justine Moore's historical-footage Flux 3 post is listed as an outlier with an all-time score of 334.07. The set also includes a separate Flux 3 cinematic-prompt demonstration.
Since the previous snapshot
What changed since Aug 13, 2026
- 85.2% of the selected posts remained.
- The creator count changed by 0.
- The leading sentiment remained stable.
How this analysis was made
Themes, sentiment, stance, and post format are classified per tweet. All counts, shares, medians, creator concentration, freshness, and performance comparisons are then calculated directly from the published snapshot.
Xholic's all-time score compares engagement while accounting for reach, post age, and creator consistency. It is used for relative comparisons within this collection.
This report analyzes the exact 27-post snapshot shown below. AI identifies editorial categories and drafts explanations; all statistics are calculated from the snapshot, and every narrative claim is checked against cited posts before publication.
Best Flux AI tweets
Top Flux AI tweets from 22 creators
Ranked 01–27
- 01
@aiwithjainam ·
🚨BREAKING: A developer just open-sourced a tool that turns any text prompt or image into a fully navigable 3D world in seconds. It's called WorldGen. You type a scene description, and within seconds you're walking through it in a browser 360° free movement, consistent geometry in every direction, real-time rendering at any camera angle you want. The technical approach is genuinely clever. Instead of trying to generate 3D geometry directly from text, WorldGen first creates a 360° panorama using FLUX.1, then lifts that panorama into a 3D Gaussian splatting representation using UniK3D. The result is a spatially consistent world you can actually explore, not just a static image with fake depth. What makes it actually usable: → Two lines of Python to generate any scene from a prompt → Image-to-scene mode turns any photo into a walkable 3D environment → Mesh generation mode for better geometry than splat output → Low VRAM mode for GPUs with less than 24GB → Background inpainting fills invisible regions as you explore → Saves output as .ply files for any standard 3D viewer 1.6k stars. Growing fast. 100% Open Source. Apache 2.0 License.
- 02
@venturetwins ·
Turns out that Flux 3 is exceptional at generating historical footage... like elementary school students in the '90s predicting how we'll use computers. (the last girl is my favorite!)
Watch video
- 03
@linoy_tsaban ·
My favorite editing model, FLUX.2 [klein] 9B, just got 2x faster: Meet FLUX.2 [klein] 9B-KV 😍💨 > Using KV-Cache Optimization to reduce computation & speed up inference by up to 2.5 times for multi-reference editing love how well it edits "around" the bullets
Watch video
- 04
@cyrildiagne ·
ml-sharp 🤝 FLUX.2 klein Inspired by @dx8152, I’ve trained a LoRA for klein 9b that can repair 3D views from ml-sharp, fixing geometry issues and restoring original details. Weights: https://t.co/NVGQc4DJIb I will share the demo + inference code soon!
Watch video
- 05
@sukh_saroy ·
🚨Two lines of code. A full explorable 3D scene generated in seconds from a text prompt. It's called WorldGen -- an open source system that converts text or images into navigable 3D scenes using Gaussian Splatting, with 360° free exploration and loop closure. Here's the full API: ```python worldgen = WorldGen() worldgen.generate_world("A beautiful landscape with a river and mountains") ``` Here's what makes it different from other text-to-3D tools: → Full 360° exploration -- generate a scene and walk through it in any direction, not just a static render → Loop closure -- the scene stays consistent as you move through it, no visual artifacts or seams → Indoor and outdoor support -- cozy bedrooms, mountain landscapes, city streets, fantasy environments → Image-to-scene mode -- upload a photo and get a walkable 3D version of it → Mesh output -- generates actual geometry you can export and use in game engines → Low-VRAM mode -- works on GPUs with as little as 10GB VRAM → Real-time rendering at any resolution with custom camera trajectory Here's the wildest part: You can give it a painting -- a flat 2D image -- and it generates a fully explorable 3D scene from it. Built on FLUX.1, Gaussian Splatting, UniK3D depth estimation, and OneFormer for segmentation. Visualized in your browser via Viser. 1.6K GitHub stars. Apache 2.0 License. 100% Open Source. (Link in the comments)
- 06
- 07
@smallfly ·
New iteration on Parallel Timelines (working title). FLUX.2-Klein 4B now runs at a satisfactory real-time speed, balancing performance and visual quality. Hand tracking controls the split, letting me define where the transformed output appears; a more gestural and playful approach than the previous eye-tracked version. #ai #realtime #realtimeai #StableDiffusion
Watch video
- 08
@emollick ·
Flux 3 is pretty darn impressive. This is what it produced with the prompt: "tracking shot that follows a female astronaut with her helmet open as she walks through a regency dance in a traditional manor, with a mural on the wall painted by Rothko. Pushing people out of the way to make room in the crowd, she then turns a corner and walks into a room paneled with hammered tin tiles and pauses as a knight and ninja fight each other without weapons. the knight is wearing brightly enameled green and white armor, she looks up and we follow her POV to a stained glass window depicting a flower and serpent, intertwined."
Watch video
- 09
- 10
- 11
@multimodalart ·
new open weights FLUX model is out @bfl_ml 🔥 FLUX.2 Klein 9B KV optimizes, kv cache of the model radically to deliver way faster edits in high quality Klein 9B always had a soft spot in my heart, with this new speed, it's now extremely useful with day 0 diffusers 🧨 & Spaces 🤗 support
- 12
@ciguleva ·
Flux vs. Nano Banana vs. Midjourney: When to Use What Midjourney: world-building, new styles, aesthetic experimentation. If that's the task, Midjourney isn't just the best option, it's the only option. Flux Klein 9B: faster and cheaper than NB 2.5 via API, wider style range than NB 2.5 (though significantly lower than Midjourney) for more experimental creative ideas. Both Flux Klein 9B and NB 2.5 have APIs; Midjourney doesn't. NB 2.5: API access, multi-subject scenes, text rendering, complex layouts, and better prompt understanding, especially for non-human characters. The downside: NB 2.5 tends to make everything too polished and plastic.
- 13
@OdinLovis ·
Virtual try-on with a single LoRA Open weight, no preprocessing, no masks, just 3 images in → dressed character out. Made with @fal Built on Flux Klein 9B. Open weights. Playground: https://t.co/99sB1a2AC2 Workflow fal with llm: https://t.co/KPMycTCmpO HuggingFace: https://t.co/PGcFCBi9v2
Watch video
- 14
- 15
@venturetwins ·
I’ve started making trailers for AI horror movies with Flux 3 This one is called “Contaminated”
Watch video
- 16
- 17
@RisingSayak ·
Last year, I got to collaborate on a number of serious projects at the intersection of Diffusers x optimization ⚡️ First, NONE of them were bootstrapped with any AI agents but pure domain knowledge and expertise. So, besides just feeling good, it's also very reassuring to me to know how important those two traits are. Now, coming to the projects that I think are worth mentioning: * `flux-fast`: Showing a combination of `torch.compile` + unscaled FP8 FA3 + no CPU-GPU sync + dynamic FP8 is great for accelerating Flux.1-*. https://t.co/Fagw9bkFPA * `torch.compile` x Diffusers: What does it take to get the most out of `torch.compile` in Diffusers across different user workloads? https://t.co/J8bPgBFK1y * `lora-fast`: How to hotswap LoRAs into compiled models without incurring (slow) recompilation issues? How to set it up for success? https://t.co/FhY8ATz4c0 * `zerogpu-brrr`: How to optimize a ZeroGPU HF Space with AOT + FA3 and other goodies? This helps save 💰 and improve the user experience of your ZeroGPU applications. https://t.co/DdPsS6O5Ky Hopefully, this will make you realize there's still a LOT that you can do (preferably pairing with AI) if you're curious and deeply invested in stuff you care about.
- 18
@shshnkp ·
With Xcode 26.4 and Neural Accelerator profiling counters, its cool to see Neural Accelerator Utilization when running your favorite MLX models. Here's Neural Accelerator Utilization running FLUX on a MacBook Pro with M5. (Example: https://t.co/jhP782MO7F) Video walkthrough: https://t.co/hlAnocXKlo
- 19
@smallfly ·
Starting a new series of real-time img2img diffusion explorations. First experiments combining FLUX.2-Klein with MediaPipe for live tracking-driven transformations. #ai #realtime #realtimeai #stablediffusion
Watch video
- 20
@cyrildiagne ·
Had a lot of fun building this fast web demo for FLUX.2 [klein], with extreme speed and glimpses of generative UI. Checkout how fast and intuitively we're able to explore visual ideas with this model. The video is at 1x speed. With the fact that it's open weights, I'm 100% sure that it will unlock an entire new class of generative UX for creatives.
Watch video
- 21
@shushant_l ·
I’m genuinely surprised most people still use one AI image model for everything. Here’s how to choose the right AI image model for every creative task. --- 1. ChatGPT Images 2.0 is the best all-purpose option for generation, editing, reasoning, and accurate text. --- 2. Google Nano Banana 2 excels at fast editing, reference consistency, product visuals, and factual imagery. --- 3. Midjourney V8.1 is ideal for cinematic, artistic, visually striking, and style-rich images. --- 4. Seedream 5.0 Pro works best for multilingual campaigns, cultural localisation, and professional advertising visuals. --- 5. Ideogram 4.0 is a strong choice for typography, posters, layouts, infographics, and readable text. --- 6. Recraft V4 Pro is built for polished graphic design, brand assets, mockups, icons, and commercial creatives. --- 7. FLUX.2 Pro is best suited for developers building custom image applications, APIs, and automated workflows. --- 8. Adobe Firefly Image Model 5 fits professional Photoshop, advertising, photography, and enterprise workflows. --- 9. Runway Gen-4 Image delivers consistent characters and scenes for storyboards, videos, and visual storytelling. --- 10. Stable Diffusion 3.5 Large offers privacy, local generation, custom models, and maximum creative control. --- To learn more, check the infographic. ---
- 22
@drawthingsapp ·
🔄 You may not have noticed our latest two updates — the newest version is Draw Things v1.20260323.0. In addition to Lightning Draft, we’ve made many detailed fixes and improvements, such as: 🔹 Updated LTX-2.3 x2 spatial upscaler to v1.1, along with improved Hires Fix logic specifically for LTX-2.3, making it more automatic in selecting x2 or x1.5 resolutions. 🔹 Support for exporting video as HEVC. 🔹 Improved performance on M5 by 2% to 10% through various optimizations to Neural Accelerator usage. 🔹 New history view with more log-like behavior. 🔹 Fixed crash for FLUX.2 [klein] 9B KV when batch size > 1 or text guidance ≠ 1. 🔹 Further fixes for video VAE speed issues at large resolutions or long frame counts.
- 23
- 24
@shawnchauhan1 ·
Open-source image generation just eliminated every closed-source advantage. Flux 2 Dev Turbo isn't just faster - it's the #1 ranked model and it's free. Midjourney built a business on quality differentiation. That moat evaporated in 2025. When the best tool is open and the speed advantage is 6x, what exactly are customers paying for? Nostalgia isn't a subscription model.
- 25
@WesRoth ·
Ollama has officially added image generation capabilities now live for macOS, with support for Windows and Linux coming soon. Users can generate photorealistic or stylized images right from their terminal using models like: Z-Image Turbo (from Alibaba’s Tongyi Lab): great at realism, bilingual text rendering (English + Chinese), and open for commercial use (Apache 2.0). FLUX.2 Klein (by Black Forest Labs): excels at text in images, UI mockups, and product visuals. Comes in 4B (open) and 9B (non-commercial) versions. Customization options include image size, random seed, number of steps, and negative prompts. Images save locally and even render inline in supported terminals like iTerm2 and Ghostty.
- 26
- 27
@willkurt ·
Okay this is cool! Totally open model for both image gen and chat running on my own hardware but available with an app-native mobile experience! - Gemma 4 26b running on an mbp - Flux running on my desktop (rtx4090) - Open Web UI to tie them all together! - Tailscale means this runs mobile anywhere!
Best Tweets by Topic