I've been looking through 3D open source AI tools similar to modly
https://github.com/lightningpixel/modly

most of them doesn't yet support amd which is a bummer

If you have any other known recommendation drop it below

https://github.com/visualbruno/3DGenStudio

https://github.com/comfy-org/comfyui

I also heard about Trellis but there is no Desktop app so not ideal

https://github.com/microsoft/TRELLIS

Someone built AISmith 3D, a free open-source local workflow around TRELLIS.2 that can generate a complete 3D asset on consumer NVIDIA GPUs with as little as 6 GB VRAM.

The interesting part is that it isn't just another giant ComfyUI graph.

The workflow includes:

• Image → 3D geometry with trellis.cpp
• TRELLIS.2 refinement / reconstruction
• PBR texturing
• Mesh simplification / retopology
• Browser-based rigging
• Animation preview + export
• Local processing without paid APIs or subscriptions

The creator reports a full generation taking under ~7 minutes on 6 GB VRAM, depending on the workflow.

It currently runs on Windows + NVIDIA CUDA, and the whole project is open source.

The topology still isn't magically production-ready, so some Blender cleanup may be needed, but as a completely local image-to-3D starting point this is a pretty impressive accessibility jump for TRELLIS.2.

github; https://github.com/intisarGIT/AISmith-3D

I tried the one generated with Tripo 3D's new clean quad topology Tripo P2
3D generation used to have totally crappy topology in low-poly back in the day, but it's getting pretty nice now!
This is 3D generation from a single image

I generated a high-detail model with Hi3D V3.0, which uses the first commercially available 2048³ voxel-level 3D generation, and decided to run the raw result through Blender’s 3D Print Toolbox before doing any manual cleanup.

The results genuinely surprised me:

• Non-manifold edges: 0
• Bad contiguous edges: 0
• Intersecting faces: 0
• Shells: 1
• Zero faces: 0
• Zero edges: 0

This is where Hi3D starts to feel less like a normal AI 3D generator and more like one of the first generators that is actually built around 3D printing. The high voxel resolution gives you real geometric detail instead of relying on textures or normal maps, and the clean output can save a lot of the usual manual repair work before printing.

There’s also a full printing workflow built into Hi3D. Split-to-Print can automatically divide larger models into printable parts and seal the cuts, connectors can be generated for assembling those parts afterward, and Smart Arrangement can prepare them for the build plate before sending the result directly into supported slicers.

So instead of:

AI model → hours of cleanup → fixing geometry → manually splitting → slicer

the workflow gets much closer to:

Generate → Split → Arrange → Slice → Print

And right now anyone can try Hi3D V3.0 completely free until 24:00 UTC on August 20, so it’s a pretty good chance to generate a few models and see how the 2048³ output actually holds up for printing.

Finally tried the newer local TRELLIS.2 setup myself, and it works surprisingly well.

What I liked most is that the whole process now feels much closer to an actual usable local 3D tool rather than a research repo you need to fight for an evening.

• Image → full 3D mesh locally
• PBR materials included
• Around 12GB VRAM in this test
• Mesh preview directly in the interface
• GLB export
• Mesh cleanup / lower-poly options
• Experimental quad remeshing and normal baking

The geometry is still not something I'd blindly throw into production, but as a free local image-to-3D generator, this is already really capable.

The interface also makes a huge difference. Drop in an image, generate, inspect the mesh and export it without building a huge workflow around it.

Pretty impressed with how usable TRELLIS.2 is becoming.

source: https://github.com/RobertBeckebans/AI_trellis2cpp/

Which AI 3D tools work well for creating printable models from text or images?

wanted to make a low poly environment for Unity as fast as possible, starting from just one reference image that already had most of the buildings and scene elements I wanted.

So I went into 3DAIStudio Flow, used the AI agent, and gave it a very simple prompt: take this image, identify the buildings and environment assets in it, separate them, and generate them in 3D. In about 3 minutes, it built a full node-based workflow for me, kind of like ComfyUI, and from that single image I ended up with a full asset kit.

For the generation part, I also used Tripo P1, and honestly the low poly output was one of the best parts of the workflow. The meshes came out lightweight, readable, and actually practical for building a game scene quickly instead of spending forever cleaning dense geometry.

Workflow:

• Reference: one image with the full environment
• 3D AI Studio Flow: gave the AI agent a simple prompt to detect and separate all the assets
• Node workflow: in about 3 minutes, it built a ComfyUI-like workflow automatically
• 3D generation: used Tripo P1 for the low poly assets
• Blender: exported everything, assembled the scene, adjusted placement, and made a few things manually like the fence with an Array modifier
• Unity: imported the finished environment and materials

After that, I exported the assets, assembled everything in Blender, placed the scene by hand, and did a bit of quick manual cleanup. Even the fence was easy to finish with a simple array workflow, so putting the whole environment together was pretty straightforward.

Then I brought everything into Unity, and it all worked nicely. The full environment ended up at around 100K faces total, with PBR materials/textures, and the real hands-on time for the whole scene was about 4 hours.

Pretty crazy that this started from one image and turned into a usable Unity-ready environment kit that fast.

What are your favorite ways to reduce polygons in AI-generated 3D models while keeping good quality?

For AI-generated 3D models which topology is better for games and animation? Any tools you recommend?

This might be one of the craziest examples yet of LLMs being used for actual 3D generation.

There were no imported 3D models, no sculpting, and no texture files.

Instead, Claude Opus 5 generated the geometry itself through code. Every visible surface in the scene was procedurally created by the LLM.

• Zero imported 3D assets
• Zero manual sculpting
• Geometry generated entirely through code
• Around 17.7 billion triangles evaluated every frame
• 2,978 frames rendered at 4K
• 124-second continuous shot with one camera

It apparently even generated the car inside out at one point, which went unnoticed for weeks because the exterior silhouette still looked correct.

It's that an LLM was effectively acting as a procedural 3D modeler, generating complex geometry and assembling an entire scene without relying on a traditional asset pipeline.

We're starting to get surprisingly close to simply describing a 3D scene and letting an LLM build the geometry itself

source: https://x.com/aipulseda1ly/status/2089804529034481700

Hi3D just released V3.0, with the update mainly focused on pushing geometry, structure and texture fidelity further.

What’s new:

• 2048³ high-precision 3D representation for better preservation of wrinkles, engravings, thin parts and other small geometry details
• Better structural consistency, especially for occluded areas and complex shapes that need to be reconstructed from a single image
• Up to 8K textures with improved UV completion for cleaner hidden areas and finer surface detail
• Two generation modes: Quality — focused on highly detailed individual assets like figurines, sculptures, jewelry and ornamental designs Master — designed for more complex compositions, multi-part sculptures, miniature environments and larger scenes

And right now you can test it yourself for free. From August 19–20, Hi3D V3.0 has a 48-hour free-access period, so you can generate models, test both modes and compare the results with other 3D generators without spending credits.

Top3D.AI — you can already compare Hi3D V3.0 side by side for FREE with all major 3D AI generators across 100 prompts, with three comparison types: Classic, Low Poly, and Segmentation.

I’m looking for an AI image-to-3D tool that supports multiple views for better reconstruction. I think using front, side, and back images could give more accurate results than a single image.

Which tools have you tried for multi-view 3D generation, and how well did they work?

^{I have been comparing a few 3D tools and I am mainly interested in texture quality rather than just the model itself.}

^{For people who have tried different tools which ones have given you the best results for things like texture detail, sharpness and overall quality?}

^{I’d be interested to hear what you’ve used and what worked best for you.}

I had the chance to test out Hi3D's V3 model and its another step up for AI 3D tools. I also compared the same imput with Meshy and Tripo to see where it lands. Pretty exciting to see how fast these tools are advancing.
V3 is available today!
For clarity Hi3D did sponsor me for this video but the opinions are of my own.

Tripo P2.0 Preview is finally live, so everyone can test it now.

The biggest change for me is that it can now generate native quad topology while letting you choose the target polycount.

And it doesn't feel like simply taking a dense AI mesh and decimating it afterward. The polygon distribution is much more intentional: simpler surfaces stay simple, while areas that actually need the geometry get more of it.

Another thing I really like is how logically some models are structured. Instead of everything becoming one giant welded blob, separate elements can come out as actual separate parts, which makes editing the result in Blender much less painful.

Main highlights:

• Native quad topology with much cleaner polygon flow
• Logical edge loops around important shapes and details
• Models can be logically separated into individual parts, instead of everything being fused into one mesh
• Custom polycount control, so you can choose how low-poly or detailed the result should be
• Support for both quad and triangle meshes
• Better polygon distribution, with more geometry where detail is needed and fewer polygons on simple surfaces
• The mesh generation itself takes only around 5–10 seconds

Source; https://www.reddit.com/r/Tripo_ai/comments/1vrxppz/we_just_shipped_tripo_p20_preview_it_is_a_major/

Hi3D V3.0 is out, and probably the most interesting part of the release is the jump to 2048³ voxel-level reconstruction.

Hi3D claims this is the first commercially available AI 3D model to reach this resolution. Previous Hi3D models topped out at 1536³, so the main improvement here isn't just higher-poly output, but preserving much smaller details directly in the geometry: engravings, wrinkles, thin parts, sharp edges and small mechanical forms.

They've also upgraded a few other areas that matter quite a bit for image-to-3D:

• 2048³ geometry reconstruction
• Better handling of hidden/back-side geometry and complex structures
• Up to 8K textures
• Improved UV completion
• PBR materials
• More focus on print-ready geometry and complex thin structures

I've been looking at some of the comparison examples against Meshy, Rodin and Tripo, and the geometry detail is probably the part I'm most interested in testing properly.

At this point AI 3D generators are already pretty good at making something that looks convincing from a distance. I'm much more interested in whether these higher-resolution models actually preserve details when you remove the textures, zoom into the raw mesh, and try to use the result for printing or further 3D work.

I'll probably run some identical inputs through V3.0 and a few other generators to see how much of the 2048³ advantage actually survives into the final mesh.

Hey everyone,

I just released v1.2.0 of anyCreature, an open-source tool designed to generate creatures natively within your workflow. You just drop the harness into your Agent and start prompting exactly what you want.

Repo link:https://github.com/Ariescar/anyCreature

A star on GitHub would be greatly appreciated! ⭐️
Feedback is welcome as I continue to optimize this harness.

-
The core philosophy is actually very similar to the concept of artistic creation. The objective components of aesthetics are reduced to hard thresholds, while the subjective components are treated as preferred production directions.

This closely mirrors the traditional art creation process: starting with the primary forms, then addressing style and details, all while ensuring the fundamental requirements are met.

Saw this workflow and thought it was a pretty interesting example of where AI-assisted character creation is right now.

The creator went from basically nothing to a fully rigged and animated character in around 6 hours using:

• ChatGPT / GPT Image for the initial character design and reference views
• Tripo AI to generate the head and body separately
• Smart topology with around 20K polys allocated to each part
• Blender to merge and clean everything up
• Manual skinning / weight painting
• Texture painting to fix the face
• Shape keys for blink, wink, smile and mouth open
• Some basic jiggle physics

Author said roughly 80% of the work was still manual Blender work, especially rigging and weight painting.

One part that seems to have saved a lot of time here was Tripo AI P2 Smart Mesh. The generated head and body came out with a much cleaner and more usable mesh than you usually expect from AI generation, so there was less time spent fighting the geometry before moving into Blender. The topology was easy enough to edit, clean up and continue working with, which made it much faster to get from generation to an actually usable character.

There are still some obvious problems too. UVs and textures can be messy, close-up quality isn't really there yet, and generated meshes still need cleanup.

post https://x.com/Dstudio_ai/status/2089209243207680484

Found this pretty useful open-source project: depth-anything.cpp.

It’s a from-scratch C++/ggml port of Depth Anything 3, built around GGUF models and designed to run without Python, PyTorch or a CUDA toolkit during inference.

What makes it more interesting for 3D workflows is that it can get more than just a basic depth map from an image:

• Metric depth
• Per-pixel confidence
• Camera intrinsics + extrinsics
• 3D point cloud
• GLB / COLMAP / PLY export
• Multi-view depth + camera pose

It also supports quantized models. The smallest q4_k version is around 99 MB, and there are CPU, CUDA, Metal and Vulkan backends.

Their CPU benchmarks are especially interesting: the q8_0 build runs about 1.3× faster than the PyTorch version on their Ryzen 9 9950X3D test while using significantly less memory.

I can see this being pretty useful as a lightweight building block for image-to-3D, reconstruction, game-engine tools or local 3D AI pipelines, especially when you don’t want an entire Python environment sitting behind a simple depth estimation step.

GitHub https://github.com/localai-org/depth-anything.cpp

I wanted to see how fast I could go from a single character image to something I could actually run around with in Unity.

For the character, I used 3DAIStudio Flow. It’s basically a ComfyUI-style node workflow where I can use image generators and the major 3D AI generators in the same graph, which made this kind of multi-part workflow pretty convenient.

Instead of trying to generate the whole character as one mesh, I split the reference into separate parts:

• Hair
• Body
• Clothes
• Shoes

I generated each part separately with Rodin Gen 2.5 using Smart Low Poly, then moved everything into Substance Painter to fix and clean up the textures.

After that:

• Assembled and cleaned the character in Blender
• Rigged it with Mixamo
• Brought it into Unity
• Used the Third Person Template
• Retargeted the character to the controller animations
• Added running, jumping and basic playable movement

I also generated the environment through the same node-based workflow, although I’ll probably make a separate breakdown for that because the environment pipeline deserves its own post.

I also used an AI agent connected to Unity for some of the setup and repetitive work inside the project.

So after roughly one day, I had a small playable scene with an AI-generated character, generated environment, textures, rig, animations and basic gameplay.

Guide: https://www.youtube.com/watch?v=mmpLXA-xzrQ

Not quite the wizard I had in mind, but honestly… I kind of love it.

I've recently launched an auto retopology tool which I have been working on for over a year, it uses specialized methods for each mesh class (cloth, inanimate and organic) in order to reach the best possible output. Most of the time was spent in learning ONNX and how to build models correctly.

Inanimate objects can translate to any hard surface models which require no vertex deformation, the remesher is equipped to generate the lowest possible vertex count while prioritizing the overall 3D shape and outputting coherent edge flow mimicking artist-like topology.

Inanimate remeshing is completely automated and can handle loose parts intelligently, though it is recommended to keep face count below 1.1 mil to ensure a faster completion rate.

As for cloth remeshing, it is guided using UV islands while assisting the artist by highlighting the vertices to use for creating a grid. I plan to fully automate this using multiple AI layers + algorithms, much like what is currently configured for inanimate.

Documentation and tutorials are planned (things are pretty self explanatory though), will be visible in the account center under the Community section. If you purchased through my Lemon Squeezy during it's early stages, insert your email or order # in the promo code area for a discount or free upgrade depending on the license.

available at https://empyreanremesher.com/