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🤯Real-time video generation just got HUGE. Introducing Helios: A 14B parameter model running at 19.5 FPS on a single H100. Cheaper, Faster, and Stronger than 1.3B models, generating minute-long videos without the usual tricks (even no quantization).

Bin Lin

1,318 subscribers

27,792 görüntüleme • 8 ay önce •via X (Twitter)

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Bin Lin profil fotoğrafı

Bin Lin8 ay önce

(1) robustness to long-video drifting without commonly used anti-drifting heuristics; (2) real-time generation without standard acceleration techniques such as KV-cache, sparse/linear attention, or quantization

أمين رعيان profil fotoğrafı

أمين رعيان8 ay önce

@ComfyUI

Nico R von der Becke 🦢 profil fotoğrafı

Nico R von der Becke 🦢8 ay önce

@camenduru Andara en una 5060ti? 🤭

Yash profil fotoğrafı

Yash8 ay önce

@grok please verify and give every details

LightShift Studio profil fotoğrafı

LightShift Studio8 ay önce

Hey there! Still watching hours of cat vids? 🚀 Helios can churn out those cute moments in seconds - time to cut your video binge-watching.

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We present MotionStream — real-time, long-duration video generation that you can interactively control just by dragging your mouse. All videos here are raw, real-time screen captures without any post-processing. Model runs on a single H100 at 29 FPS and 0.4s latency.

We present MotionStream — real-time, long-duration video generation that you can interactively control just by dragging your mouse. All videos here are raw, real-time screen captures without any post-processing. Model runs on a single H100 at 29 FPS and 0.4s latency.

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StreamDiT Real-Time Streaming Text-to-Video Generation StreamDiT enables real-time text-to-video generation at 16 FPS on a single GPU (H100)

AK

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Helios Real Real-Time Long Video Generation Model paper:

Helios Real Real-Time Long Video Generation Model paper:

AK

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🚀 We open-sourced LongLive — interactive, real-time long-video generation. 👥Generates video in real time as users enter text prompts. ⚡️20.7 FPS on a single H100,⏱️up to 240s per clip. 🎬Fine-tunes SOTA short-video models (e.g., Wan) into long-video generators. 🌍One step closer to World Models. All code for training & inference, model weights, demo page, and videos released! Paper: Code: Model: Demo Page: Introduction Video:

🚀 We open-sourced LongLive — interactive, real-time long-video generation. 👥Generates video in real time as users enter text prompts. ⚡️20.7 FPS on a single H100,⏱️up to 240s per clip. 🎬Fine-tunes SOTA short-video models (e.g., Wan) into long-video generators. 🌍One step closer to World Models. All code for training & inference, model weights, demo page, and videos released! Paper: Code: Model: Demo Page: Introduction Video:

Yukang Chen

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Introducing The Matrix --- a foundation world model for generating infinite-length, hyper-realistic videos with real-time, frame-level control: - Infinite-length video generation - 720p high-quality rendering - Real-time, frame-level control at 16 FPS - Generalization to real-world video control 🔗Blog: 📄Paper: 💻Code & Playable Demo: Coming soon! Key Innovation: A brand new technique called the shift-window denoise process model, enabling auto-regressive generation for diffusion and consistency models in real-time. Special thanks to project leader Ruili Feng and the entire Matrix team for their dedication and hard work over the year-long project.

Hongyang Zhang

178,482 görüntüleme • 1 yıl önce

Seedance 2 just dropped as open-source.!.. ok, mostly... Helios - 14B model for minute-scale vid gen. - high-quality, fast -No KV-cache, no quantization, no TinyVAE, just pure architectural efficiency. - T2V/I2V/V2V ready.

Seedance 2 just dropped as open-source.!.. ok, mostly... Helios - 14B model for minute-scale vid gen. - high-quality, fast -No KV-cache, no quantization, no TinyVAE, just pure architectural efficiency. - T2V/I2V/V2V ready.

Wildminder

25,251 görüntüleme • 8 ay önce

LTX-Video new text-to-video model generates stunning, high-quality videos faster than real-time—5 seconds of 24fps video at 768x512 in just 4 seconds on an Nvidia H100 open code & weights

LTX-Video new text-to-video model generates stunning, high-quality videos faster than real-time—5 seconds of 24fps video at 768x512 in just 4 seconds on an Nvidia H100 open code & weights

AK

51,498 görüntüleme • 1 yıl önce

Introducing VEED Fabric 1.0. The world’s first AI talking video model. Built for creating great-looking videos, FAST. • Create 1-minute-long videos • 60x cheaper • 7x faster Repost = Full guide in DMs.

Introducing VEED Fabric 1.0. The world’s first AI talking video model. Built for creating great-looking videos, FAST. • Create 1-minute-long videos • 60x cheaper • 7x faster Repost = Full guide in DMs.

VEED | AI Video Creation

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60-second AI video generation just got unlocked! LTXV is the first model to generate native long-form video, with controllability that beats every open source model. - 8× longer than typical gen video - 10–100× faster & cheaper - Runs even on consumer GPUs - Pose, depth & control LoRAs supported Available now. Go try it >>

60-second AI video generation just got unlocked! LTXV is the first model to generate native long-form video, with controllability that beats every open source model. - 8× longer than typical gen video - 10–100× faster & cheaper - Runs even on consumer GPUs - Pose, depth & control LoRAs supported Available now. Go try it >>

LTX

545,455 görüntüleme • 1 yıl önce

Introducing LingBot-World: An open-source world simulator pushing the boundaries of video generation. 🚀 🌍 High-Fidelity: Realistic, scientific, & stylized. 🧠 Long-Term Memory: Minute-level consistency. ⚡ Real-Time: <1s latency at 16 FPS. 📜 Apache 2.0 Licensed. Model: Github:

Introducing LingBot-World: An open-source world simulator pushing the boundaries of video generation. 🚀 🌍 High-Fidelity: Realistic, scientific, & stylized. 🧠 Long-Term Memory: Minute-level consistency. ⚡ Real-Time: <1s latency at 16 FPS. 📜 Apache 2.0 Licensed. Model: Github:

ModelScope

28,809 görüntüleme • 9 ay önce

LiveTalk: A real-time multimodal avatar that streams video at ~25 FPS; - OmniAvatar-1.3B + Qwen3-Omni.

Wildminder

29,414 görüntüleme • 10 ay önce

Meet LingBot-World 2.0.🌍A 1.3B world model, running continuous interactive generation in real time on a single consumer GPU. 🤖 ⚡ It responds to movement, camera control, combat, and text-driven events in real time, while the scene keeps unfolding instead of ending as a fixed video clip. 🌌 Causal pretraining and MoBA help preserve textures, geometry, and scene consistency over long autoregressive rollouts. 🧠 Consistency and distribution-matching distillation compress multi-step generation and train the model on its own rollouts, reducing accumulated drift. 🛠️ The 14B Causal Pretrain backbone and Bidirectional teacher are also open, giving developers a path to post-train, distill, compress, and adapt new world models. 🔒 CC BY-NC-SA 4.0. Non-commercial use only.

Meet LingBot-World 2.0.🌍A 1.3B world model, running continuous interactive generation in real time on a single consumer GPU. 🤖 ⚡ It responds to movement, camera control, combat, and text-driven events in real time, while the scene keeps unfolding instead of ending as a fixed video clip. 🌌 Causal pretraining and MoBA help preserve textures, geometry, and scene consistency over long autoregressive rollouts. 🧠 Consistency and distribution-matching distillation compress multi-step generation and train the model on its own rollouts, reducing accumulated drift. 🛠️ The 14B Causal Pretrain backbone and Bidirectional teacher are also open, giving developers a path to post-train, distill, compress, and adapt new world models. 🔒 CC BY-NC-SA 4.0. Non-commercial use only.

ModelScope

34,080 görüntüleme • 1 ay önce

🚨 2.8 trillion parameters. Under 4GB VRAM. No quantization. An open source tool called AirLLM has changed how large language models run on consumer hardware. Instead of loading the entire model at once, it processes one layer at a time. This means your VRAM needs depend only on the size of a single layer rather than the full model. No quantization. No distillation. No pruning. → DeepSeek V3 (671B) runs on just 12GB → Llama 3.1 405B runs on 8GB → Kimi K3 (2.8 trillion parameters) runs on under 4GB → Works with nearly every major open source model The largest model often needs the least VRAM. Kimi K3 is a sparse mixture of experts model, so it only loads the specific experts activated by each token instead of an entire dense layer. This is why a 2.8 trillion parameter model can run in less memory than a 70B model. AirLLM makes frontier scale AI practical on everyday hardware without any of the usual tradeoffs. (Link in the comments)

🚨 2.8 trillion parameters. Under 4GB VRAM. No quantization. An open source tool called AirLLM has changed how large language models run on consumer hardware. Instead of loading the entire model at once, it processes one layer at a time. This means your VRAM needs depend only on the size of a single layer rather than the full model. No quantization. No distillation. No pruning. → DeepSeek V3 (671B) runs on just 12GB → Llama 3.1 405B runs on 8GB → Kimi K3 (2.8 trillion parameters) runs on under 4GB → Works with nearly every major open source model The largest model often needs the least VRAM. Kimi K3 is a sparse mixture of experts model, so it only loads the specific experts activated by each token instead of an entire dense layer. This is why a 2.8 trillion parameter model can run in less memory than a 70B model. AirLLM makes frontier scale AI practical on everyday hardware without any of the usual tradeoffs. (Link in the comments)

Brooks Whale X 🐋

40,529 görüntüleme • 22 gün önce

Introducing RTFM (Real-Time Frame Model): a highly efficient World Model that generates video frames in real time as you interact with it, powered by a single H100 GPU. RTFM renders persistent and 3D consistent worlds, both real and imaginary. Try our demo of RTFM today!

Introducing RTFM (Real-Time Frame Model): a highly efficient World Model that generates video frames in real time as you interact with it, powered by a single H100 GPU. RTFM renders persistent and 3D consistent worlds, both real and imaginary. Try our demo of RTFM today!

World Labs

342,124 görüntüleme • 1 yıl önce

A breakthrough in real-time video generation. As a research preview developed with NVIDIA and shared at NVIDIAGTC this week, we trained a new real-time video model running on Vera Rubin. HD videos generate instantly, with time-to-first-frame under 100ms. Unlocking an entirely new creative paradigm and bolstering the foundations of our General World Model, GWM-1. Real-time generation opens a fundamentally different design space for video models and world simulation. We're investing in co-designing our models alongside advances in hardware to keep pushing this frontier.

A breakthrough in real-time video generation. As a research preview developed with NVIDIA and shared at NVIDIAGTC this week, we trained a new real-time video model running on Vera Rubin. HD videos generate instantly, with time-to-first-frame under 100ms. Unlocking an entirely new creative paradigm and bolstering the foundations of our General World Model, GWM-1. Real-time generation opens a fundamentally different design space for video models and world simulation. We're investing in co-designing our models alongside advances in hardware to keep pushing this frontier.

Runway

1,166,679 görüntüleme • 7 ay önce

Excited to announce LTX-Video! Our new text-to-video model generates stunning, high-quality videos faster than real-time—5 seconds of 24fps video at 768x512 in just 4 seconds on an Nvidia H100! ⚡ We’re open-sourcing the code & weights. Check out the results 🎥👇

Excited to announce LTX-Video! Our new text-to-video model generates stunning, high-quality videos faster than real-time—5 seconds of 24fps video at 768x512 in just 4 seconds on an Nvidia H100! ⚡ We’re open-sourcing the code & weights. Check out the results 🎥👇

Yoav HaCohen

50,447 görüntüleme • 1 yıl önce

Introducing Faster Qwen3TTS! Realistic voice generation at 4x real time: - Same amazing voice quality from Qwen's model - Streaming support with <200 ms to first audio - 5x faster than the official implementation Just pip install faster-qwen3-tts Try the demo!

Introducing Faster Qwen3TTS! Realistic voice generation at 4x real time: - Same amazing voice quality from Qwen's model - Streaming support with <200 ms to first audio - 5x faster than the official implementation Just pip install faster-qwen3-tts Try the demo!

Andi Marafioti

92,691 görüntüleme • 8 ay önce

Our research team just released Flex-Forcing: a video generation method that lets a single model switch between generation methods at inference time. Right now there are two main approaches to video generation. Bidirectional diffusion models attend to every frame at once, holding structure well at the cost of speed. Autoregressive models generate frame by frame, so they stream fast and scale to long clips, but accumulate error and drift over time. Flex-Forcing trains a single model to do both, letting you choose from the range at inference based on your compute budget.

Our research team just released Flex-Forcing: a video generation method that lets a single model switch between generation methods at inference time. Right now there are two main approaches to video generation. Bidirectional diffusion models attend to every frame at once, holding structure well at the cost of speed. Autoregressive models generate frame by frame, so they stream fast and scale to long clips, but accumulate error and drift over time. Flex-Forcing trains a single model to do both, letting you choose from the range at inference based on your compute budget.

NVIDIA AI

31,412 görüntüleme • 4 ay önce

Whoa, this is Temporal Gaussian Hierarchy (TGH). This AI can real-time render long volumetric videos in 1080p at 450 fps on a single RTX 4090 GPU. And 18,000 frames (around 10 minutes) long 🤯 7 wild demos: 1. Real-time demos on MobileStage dataset

Whoa, this is Temporal Gaussian Hierarchy (TGH). This AI can real-time render long volumetric videos in 1080p at 450 fps on a single RTX 4090 GPU. And 18,000 frames (around 10 minutes) long 🤯 7 wild demos: 1. Real-time demos on MobileStage dataset

Min Choi

464,231 görüntüleme • 1 yıl önce