Text-to-video model from scratch (2 brothers, 2 years, 2B params)
Writeup (includes good/bad sample generations): https://www.linum.ai/field-notes/launch-linum-v2 We're Sahil and Manu, two brothers who spent the last 2 years training text-to-video models from scratch. Today we're releasing them under Apache 2.0. These are 2B param models capable of generating 2-5 seconds of footage at either 360p or 720p. In terms of model size, the closest comparison is Alibaba's Wan 2.1 1.3B. From our testing, we get significantly better motion capture and aesthetics. We're not claiming to have reached the frontier. For us, this is a stepping…
Text-to-video model from scratch (2 brothers, 2 years, 2B params) launched on January 22, 2026 with 158 votes, #194 of 14,584 launches that month and more than 95% of that year's launches.
In plain words
Linum is a text-to-video model developed by two brothers over two years, released under Apache 2.0. The 2-billion-parameter model generates 2-5 seconds of video at 360p or 720p resolution from text descriptions. According to the creators, it demonstrates better motion capture and visual quality compared to similarly-sized models like Alibaba's Wan 2.1. The model is available for developers and researchers to use and build upon.
written from the facts on this page · September 2026
From the sources
360p or 720p, 2-5 seconds, Apache 2.0
In the maker’s words, at launch
Writeup (includes good/bad sample generations): https://www.linum.ai/field-notes/launch-linum-v2 We're Sahil and Manu, two brothers who spent the last 2 years training text-to-video models from scratch. Today we're releasing them under Apache 2.0. These are 2B param models capable of…
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Apple's SHARP running in the browser via ONNX runtime webMay 2026 · github.com · ▲185Hi HN, author here. SHARP is Apple's recent single-image 3D Gaussian splatting model (https://arxiv.org/abs/2512.10685). Their reference code is PyTorch + a pretty heavy pipeline; I wanted to see if it could run in a browser with no server hop, so I exported the predictor to ONNX and ran it via onnxruntime-web with the WebGPU EP. What works: drop in an image, get a .ply you can download or preview live, all on your machine — your image never leaves the tab. The model is large (~2.4 GB sidecar) so first load is slow on a cold cache, but inference itself is a few seconds on…
LTX.bio2021 · lightricks.com · ▲164Hey HN, after our 13B release we've been working on a faster version of our open-source video model and we're excited to share it. We started with a 13B base model that already had competitive generation speeds (e.g. 55s for a 5s video on an H100 — faster than any other model out there). But we wanted to push it further to allow everyone to quickly iterate over their video generations. So we built a distilled version focused on speed without sacrificing temporal or spatial coherence. With the Distilled model, you can now generate 5-second 720p videos in about 9.5 seconds on an H100, and…

Hotshot – 4 Person Team Builds a State of the Art Video Model2024 · hotshot.co · ▲26Hi HN! We're proud to share Hotshot, a large-scale diffusion transformer model for text-to-video generation that we built with just a 4-person team. You can try it today in beta at https://hotshot.co, with 2 free generations per day. The model generates 5 seconds of 720p video from text prompts. It excels at prompt alignment, and consistency. It also excels at generating people, animals, and nature. In blind tests with 100 users, Hotshot generations were preferred to Runway ML 60% of the time. Hotshot generations were preferred to Luma 80% of the time. Overall, users preferred…
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