• A new Vanilla trainer (msplat is dropped) Vanilla now runs on the same Metal engine as MCMC, with the proven settings of the gsplat project. Dense detail trains in full, it uses less memory, and when the splat budget is Unlimited it stops adding splats at what your Mac can hold instead of running out. Existing projects open and train with it unchanged. • The viewport fills the window The live view now always fills the viewport's width. A wider window shows more of the scene to the sides instead of black bars, and the point cloud and the splats stay framed alike. • A realistic time left Training slows down as the scene grows and the images reach full size, and the time left now allows for it from the start, rather than promising a minute for a five-minute run. A "~" marks it while it may still change.

Faster camera solving — feature matching now runs on the GPU and checks every feature, for slightly more detail. Switch it off in the sparse settings to match on the CPU. Leaner bundle adjustment — the scene is refined less often as it grows, cutting that stage by about a third with the same accuracy.

(1.1.1) Bug Fix • Large captures are caught before they load A capture too big for your Mac's memory could make the app quit as training started. It is now checked before any images load, and if it won't fit you're told which Training resolution will. • Vanilla training stops before memory runs out Vanilla grows splats as far as the scene asks. It now stops at what your Mac can hold alongside the images, and keeps everything trained so far. • The live viewport steps aside If the GPU can't spare memory for the live viewport, it switches off with a note in the console and training carries on. (1.1.0) New Features • A second trainer: MCMC • Splat budgets • Training resolution • Help on every setting • The live viewport, on from the start • Half the memory for Vanilla training • Finished scenes open faster

(1.1.0) • A second trainer: MCMC Choose Vanilla or MCMC for any project. MCMC trains a fixed budget of splats, moving faded ones to where the scene needs them, so memory is known before it starts. Available from the command line and to AI assistants too. • Splat budgets Cap how many splats either trainer uses, from 100k to 100M. A budget this Mac can't hold is marked in the menu and refused before any images load, rather than grinding into swap. • Training resolution One setting caps the image size both trainers work from — most useful for imported reconstructions that link full-size photos. Native keeps the images as they are. • Help on every setting A ? beside each setting explains what it does and what each choice means. • The live viewport, on from the start It now renders every scene through one sharper renderer: dense areas no longer drop splats, empty space is black, and orbiting stays smooth while training runs. The coarse-to-fine schedule keeps running with the viewport on. • Half the memory for Vanilla training Training images are held at a quarter of their former size, roughly halving what a large capture needs. • Finished scenes open faster Viewing a saved scene no longer loads the training images — just the scene and its cameras.

WHAT'S NEW (1.0.4) • Command line Drive the app from a script: run a capture, import a reconstruction, or run a saved batch, with JSON results for pipelines. The App Store copy authorises a folder once, then works beneath it. • AI assistants An MCP server, so Claude and other assistants can build a splat, follow it as it trains, report on projects already finished, and advise on a capture before you shoot it. • Drone propellers Trim edges keeps the rim of each fisheye lens out of camera tracking; Crop edges takes it out of the images that train. Each masking control now says whether it changes the solve or the splat. • Readable over bright scenes The scene panel and the sparse/splat switch no longer wash out against a sky. • Stopping actually stops Cancelling during the load used to be ignored until the whole scene had reached the GPU. It now stops as soon as the load ends, and says what it is waiting for. A stopped run reads as stopped, not as a pipeline error. • Large captures load leaner A scene is no longer held several times over while it loads, cutting peak memory by about a third — so a big project is less likely to push the Mac into swap.

v1.0.3 • Fixed Colmap rig support. • Fixed New from Media recursive dir. v1.0.2 • Insta360 .insv Dual-fisheye clips import directly, both lenses solved. The camera operator can be masked out so they don't train in as floaters. • Several videos in one scene Mix as many clips as you like — ordinary video and 360° footage together. • Batch processing Queue captures and leave the Mac to it, each its own project with its own settings. The queue saves itself, so an interrupted run resumes where it stopped: finished projects skipped, failed ones retried. • Batches accept COLMAP data A folder that already holds a reconstruction goes straight to training. • Training log Each run appends splat count, quality, duration and peak memory to output-log.txt. • Leaner memory Fixed a leak that grew GPU memory for the length of a run — peak usage down by about two thirds. A RAM readout in the status bar shows what the current run is using.

v1.0.2 • Insta360 .insv Dual-fisheye clips import directly, both lenses solved. The camera operator can be masked out so they don't train in as floaters. • Several videos in one scene Mix as many clips as you like — ordinary video and 360° footage together. • Batch processing Queue captures and leave the Mac to it, each its own project with its own settings. The queue saves itself, so an interrupted run resumes where it stopped: finished projects skipped, failed ones retried. • Batches accept COLMAP data A folder that already holds a reconstruction goes straight to training. • Training log Each run appends splat count, quality, duration and peak memory to output-log.txt. • Leaner memory Fixed a leak that grew GPU memory for the length of a run — peak usage down by about two thirds. A RAM readout in the status bar shows what the current run is using.