Takes an image, multiple images, panorama or video plus a camera path and generates a video walking through the scene. Code released, based on Wan 2.1 1.3B, under 6 GB.
Spatial world model that turns images, panoramas or video plus a camera path into explorable, consistent novel-view video.
Updated EU status checked Last shown
InSpatio World 1.5 at a glance
- What is InSpatio World 1.5?
- InSpatio World 1.5 is a model from InSpatio. Spatial world model that turns images, panoramas or video plus a camera path into explorable, consistent novel-view video.
- Who makes InSpatio World 1.5?
- InSpatio World 1.5 is made by InSpatio.
- Does InSpatio World 1.5 work in the EU?
- Available in the EU. Code is described as released as open source and can be run locally, so there is no apparent regional restriction; no explicit EU statement or license text was found. Last verified 14 Nov 2026.
- How much does InSpatio World 1.5 cost?
- Open source, open source. Project page states code is released as open source; no pricing information found.
- Where was InSpatio World 1.5 shown?
- In 1 creator video by AI Search. Most recently by AI Search on 4 Oct 2026, at 0:48 in “Gemini 4, GPT 6.1, Plasma conjecture, Napoleon code solved, OpenAI Dots, Claude Sonnet 5.5: AI NEWS”.
Sources: the vendor's own pages (linked above) and creator videos at the linked timestamps. EU status is information, not legal advice; see how we check.
InSpatio-World 1.5 is a model from InSpatio that generates novel-view video from a source scene. It accepts a single image, a set of images, a panorama or a video, and renders a camera path through the scene, including areas hidden in the original view. Version 1.0 worked from a single video; 1.5 extends the inputs and supports wider viewpoint changes.
The project emphasises consistency of subject identity, spatial structure and style as the camera moves and, for video input, as time advances. Stated use cases include cinematography, bullet-time sequences from multiple synchronized images, immersive experiences, and research in spatial and embodied intelligence. It is trained for next-view prediction on large-scale data from dynamic real-world scenes.
According to a YouTube creator summary, the released code is based on Wan 2.1 1.3B and runs in under 6 GB. The project page says it is available to try and that the code is released as open source. No license, repository or weights links were found in the provided material, so those details are unverified.
- Inputs: single image, multi-image set, panorama or video
- Camera-path-controlled novel-view video generation
- Reveals regions hidden from the original viewpoint
- Preserves identity, spatial structure and style across large viewpoint changes
- Bullet-time sequences from synchronized multi-image input
- Reportedly based on Wan 2.1 1.3B with low VRAM needs
As seen on YouTube
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