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LightVAE + ComfyUI node: High-performance video VAE; runs 2–3x faster using 50% less memory; LightTAE offers a 10+x speedup on just ~0.4GB VRAM

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Wildminder

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38,092 görüntüleme • 7 ay önce •via X (Twitter)

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Microsoft just a 1-bit LLM with 2B parameters that can run on CPUs like Apple M2. BitNet b1.58 2B4T outperforms fp LLaMA 3.2 1B while using only 0.4GB memory versus 2GB and processes tokens 40% faster. 100% opensource.
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Microsoft just a 1-bit LLM with 2B parameters that can run on CPUs like Apple M2. BitNet b1.58 2B4T outperforms fp LLaMA 3.2 1B while using only 0.4GB memory versus 2GB and processes tokens 40% faster. 100% opensource.

Shubham Saboo

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Elevate your ComfyUI video outputs this fall. 🚀 Launching with RTX Spark, RTX Video Frame Generation arrives as a ComfyUI node and Python wheel. Multiply frame rates to turn choppy 15-20 fps outputs into smooth, high-quality playback.
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Elevate your ComfyUI video outputs this fall. 🚀 Launching with RTX Spark, RTX Video Frame Generation arrives as a ComfyUI node and Python wheel. Multiply frame rates to turn choppy 15-20 fps outputs into smooth, high-quality playback.

NVIDIA RTX Spark

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Introducing Steerable Motion, a ComfyUI custom node for steering videos using batches of images. You provide images & instructions on how you want to travel between them and it creates smooth video to fill in the gaps. See attached + more here:
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Introducing Steerable Motion, a ComfyUI custom node for steering videos using batches of images. You provide images & instructions on how you want to travel between them and it creates smooth video to fill in the gaps. See attached + more here:

POM

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Introducing #Ray2 Flash—3x faster, 3x cheaper new model. Flash brings Ray’s frontier production-ready Text-to-Video, Image-to-Video, audio, and control capabilities with high quality and speed to all subscribers—so you can create more, faster, and without limits. Available now.
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Introducing #Ray2 Flash—3x faster, 3x cheaper new model. Flash brings Ray’s frontier production-ready Text-to-Video, Image-to-Video, audio, and control capabilities with high quality and speed to all subscribers—so you can create more, faster, and without limits. Available now.

Luma

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Our video editing model Lucy-Edit just got way better. 2× faster, half the price (and open source). More control, faster performance, and seamless results.
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Our video editing model Lucy-Edit just got way better. 2× faster, half the price (and open source). More control, faster performance, and seamless results.

Decart

814,369 görüntüleme • 7 ay önce

🎉 The built-in node help menu is now available to everyone. 🔁 Just update your ComfyUI to the latest version and make sure the frontend is at least v1.22.2
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🎉 The built-in node help menu is now available to everyone. 🔁 Just update your ComfyUI to the latest version and make sure the frontend is at least v1.22.2

ComfyUI

16,735 görüntüleme • 1 yıl önce

A little side-by-side comparison, one using the Wan model in ComfyUI, the other using Luma Ray 2.
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A little side-by-side comparison, one using the Wan model in ComfyUI, the other using Luma Ray 2.

enigmatic_e

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(◑‿◐) You'd think you can't make the classics better. Try using LTX cross eye IC Lora on ComfyUI
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(◑‿◐) You'd think you can't make the classics better. Try using LTX cross eye IC Lora on ComfyUI

ComfyUI

23,362 görüntüleme • 4 gün önce

✨ Free ComfyUI Workflow for Clarity Upscaler! Finally, we have a fully ComfyUI workflow that runs locally on your own GPU and uses the same technology as Clarity To use it, just download the free-workflow.json file from the ComfyUI-ClarityAI repo 😀 Ad: If you're looking for a more convenient way to upscale, try my app: 👩‍💻 App: 🐰 ComfyUI:
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✨ Free ComfyUI Workflow for Clarity Upscaler! Finally, we have a fully ComfyUI workflow that runs locally on your own GPU and uses the same technology as Clarity To use it, just download the free-workflow.json file from the ComfyUI-ClarityAI repo 😀 Ad: If you're looking for a more convenient way to upscale, try my app: 👩‍💻 App: 🐰 ComfyUI:

philz1337x

75,601 görüntüleme • 1 yıl önce

Free Blender AI Motion Capture Plugin: Runs a 1-billion-parameter model on a GPU with 8GB VRAM, supporting real-time capture and video uploads — no cost required.
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Free Blender AI Motion Capture Plugin: Runs a 1-billion-parameter model on a GPU with 8GB VRAM, supporting real-time capture and video uploads — no cost required.

CYANPUPPETS

15,761 görüntüleme • 1 yıl önce

We just launched a 3x performance improvement for our order book interface. Pre-batched messages (12x fewer msgs to parse), less GC pressure, lower CPU, leading to a much snappier ActiveTrader experience (old on left, new on right). More improvements incoming.
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We just launched a 3x performance improvement for our order book interface. Pre-batched messages (12x fewer msgs to parse), less GC pressure, lower CPU, leading to a much snappier ActiveTrader experience (old on left, new on right). More improvements incoming.

Tyler Winklevoss

48,762 görüntüleme • 3 ay önce

MiniMax just dropped M2.5 and it's on par with Opus 4.6 while being 20x cheaper and 3x faster???
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MiniMax just dropped M2.5 and it's on par with Opus 4.6 while being 20x cheaper and 3x faster???

shydev

442,571 görüntüleme • 4 ay önce

I ported DepthCrafter to ComfyUI! 🔥 Now you can generate super stable depthmap videos from any input video. The VRAM requirement is pretty high (>16GB) if you want to render long videos in high res (768p and up) It pairs well with Depthflow! Repo link in comments below👇
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I ported DepthCrafter to ComfyUI! 🔥 Now you can generate super stable depthmap videos from any input video. The VRAM requirement is pretty high (>16GB) if you want to render long videos in high res (768p and up) It pairs well with Depthflow! Repo link in comments below👇

akatz

1,878,404 görüntüleme • 1 yıl önce

See how Half-Life 2 looks like running on just 8 MB of VRAM, which is 8 times less than the GPUs of its time, brought to you by Budget Builds. It's 60 FPS:
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See how Half-Life 2 looks like running on just 8 MB of VRAM, which is 8 times less than the GPUs of its time, brought to you by Budget Builds. It's 60 FPS:

80 LEVEL

11,493 görüntüleme • 1 yıl önce

The first natively trained 1-bit model: BitNet 2B. Trained on 4 trillion tokens. that can run on CPUs like Apple M2 Native 1.58-bit weights and 8bit activations W158A8 Outperforms LLaMA &close to Qwen 2.5 1.5B in while using only 0.4GB memory versus 2GB and processes tokens 40%
0:13

The first natively trained 1-bit model: BitNet 2B. Trained on 4 trillion tokens. that can run on CPUs like Apple M2 Native 1.58-bit weights and 8bit activations W158A8 Outperforms LLaMA &close to Qwen 2.5 1.5B in while using only 0.4GB memory versus 2GB and processes tokens 40%

Md Ismail Šojal 🕷️

43,647 görüntüleme • 3 ay önce

OK the Nexus CLI has some fixes deployed: - Given a Node ID, it runs end-to-end Node ID generation on the Nexus OS is still getting fixed.
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OK the Nexus CLI has some fixes deployed: - Given a Node ID, it runs end-to-end Node ID generation on the Nexus OS is still getting fixed.

Daniel Marin | nexus.xyz

108,636 görüntüleme • 1 yıl önce

MTP speedup Qwen by 2.5x in Atomic Chat Dense vs MoE models on 2x RTX 5090 Qwen3.6 27B: 51 → 117 tps +137% Qwen3.6 35B-A3B: 218 → 267 tps +25% MTP drafts several tokens ahead and verifies them in one pass. The speedup depends on memory moved per pass. Dense 27B reads all 27B params per token, MoE 35B-A3B only reads 3B active. Dense had way more to save by batching. The baseline tps also differ (218 vs 51) for the same reason from the other side. Token generation is memory-bandwidth bound, and MoE moves ~8x less memory per token, so its baseline is already 4x ahead. ~80% draft acceptance. Zero accuracy loss. ~1 GB extra VRAM. Open-source code and local AI app – in the comments 👇
0:14

MTP speedup Qwen by 2.5x in Atomic Chat Dense vs MoE models on 2x RTX 5090 Qwen3.6 27B: 51 → 117 tps +137% Qwen3.6 35B-A3B: 218 → 267 tps +25% MTP drafts several tokens ahead and verifies them in one pass. The speedup depends on memory moved per pass. Dense 27B reads all 27B params per token, MoE 35B-A3B only reads 3B active. Dense had way more to save by batching. The baseline tps also differ (218 vs 51) for the same reason from the other side. Token generation is memory-bandwidth bound, and MoE moves ~8x less memory per token, so its baseline is already 4x ahead. ~80% draft acceptance. Zero accuracy loss. ~1 GB extra VRAM. Open-source code and local AI app – in the comments 👇

atomic.chat

169,430 görüntüleme • 1 ay önce

60fps Wan 2.2 I2V + GPT Image 2.0 in ComfyUI with the SYSTMS TimeSlice node (dropping this week)
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60fps Wan 2.2 I2V + GPT Image 2.0 in ComfyUI with the SYSTMS TimeSlice node (dropping this week)

Ingi Erlingsson 🪄

12,387 görüntüleme • 16 gün önce

Griffain is now 3x faster
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Griffain is now 3x faster

griffain

193,168 görüntüleme • 1 yıl önce