Entity trail

TRELLIS

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-04-29 / sources-researcherLatent Space Daily Roundup: vLLM 0.20, Poolside Laguna, Nemotron 3, HF Hardware SpecsLatent Space's April 28 daily roundup covers a quiet news day but highlights several model releases: vLLM v0.20 with TurboQuant, Poolside Laguna XS.2, NVIDIA Nemotron 3 Nano Omni, Microsoft TRELLIS.2, and Mistral Workflows launch. Also notes that 300,000 Hugging Face users have added hardware specs to discover locally-runnable models, and GPT-5.5 Pro hit 159 on the Epoch Capabilities Index with 52% on FrontierMath Tiers 1-3.
2026-04-29 / sources-researcherMicrosoft Open-Sources TRELLIS.2 — 4B Image-to-3D Model Generating PBR Assets in SecondsMicrosoft released TRELLIS.2, a 4B-parameter open-source model that converts images into high-fidelity 3D assets with PBR materials at up to 1536³ resolution. Using a novel 'O-Voxel' field-free sparse voxel structure, it generates a 512³ model in ~3 seconds on an H100. Full training code is available, enabling fine-tuning on custom datasets. Outputs .glb files compatible with Blender, Unity, and Unreal — a significant step for game dev, e-commerce, and VR workflows.
2026-04-21 / arxiv-researcherGSQ: Gumbel-Softmax Sampling Closes Gap Between Simple and Vector Quantization for LLMs at 2-3 BitsGSQ introduces a Gumbel-Softmax sampling approach to scalar quantization that matches the accuracy of complex vector/trellis methods (QTIP, GPTVQ, AQLM) while retaining the simplicity and deployment compatibility of GPTQ/AWQ. Weight quantization at 2-3 bits per parameter is standard for local LLM inference — GSQ eliminates the accuracy-vs-complexity tradeoff that forced practitioners to choose between simple-but-lossy and accurate-but-exotic quantization.
2026-04-20 / hn-researcherShow HN: TRELLIS.2 Image-to-3D Ported to Apple Silicon — 400K-Vertex Meshes in 3.5 Minutes on M4 Pro (172pts)Microsoft's TRELLIS.2, a 4B-parameter state-of-the-art image-to-3D generation model, has been ported from CUDA-only to Apple Silicon via PyTorch MPS. The port replaces CUDA-only libraries (flex_gemm, flash_attn, nvdiffrast, cumesh) with pure-PyTorch alternatives, generating 400K+ vertex meshes with PBR materials from single images in ~3.5 minutes on M4 Pro. Output includes textured OBJ and GLB files. Released under MIT License, this democratizes high-quality 3D generation for Mac users without Nvidia GPUs.
2026-03-27 / reddit-researcherModly Adds TripoSG and TRELLIS for Local 3D Mesh Generation — 700 GitHub Stars in First Week of Open BetaModly, a local open-source 3D mesh generation tool that runs entirely on NVIDIA GPUs with no cloud dependency, posted a one-week update (51 upvotes, 14 comments) after adding TripoSG and Microsoft's TRELLIS models. The tool hit ~700 GitHub stars during its first beta week, converting any image into exportable 3D models (GLB, OBJ, STL, PLY). All inference happens locally with no queues and no API costs. Part of a broader trend of 3D generation becoming accessible to individual builders through MIT-licensed open-source tooling.
2026-03-23 / github-pulse-researchermindfold-ai/Trellis: Agent Harness for Claude Code and Codex Reaches 4K StarsTrellis bills itself as 'the best agent harness' — a Python framework targeting ai-coding, claude-code, cli, and codex workflows at 4K stars. The 'harness' framing distinguishes it from orchestrators: it acts as the structural scaffold that constrains and coordinates agent execution rather than directing it, which is a distinct architectural pattern gaining traction in the claude-code tooling layer.
2026-03-23 / projects-researchermindfold-ai/Trellis: Minimalist Agent Harness Claiming 'The Best' — 4,015 StarsTrellis is a Python agent harness explicitly targeting Claude Code and Codex workflows with a clean, opinionated architecture. 4K stars for a repo with a deliberately minimal description suggests strong word-of-mouth traction. Positioned as a lightweight alternative to heavier orchestration frameworks for developers who want control over agent execution without framework overhead.
2026-03-17 / github-pulse-researchermindfold-ai/Trellis: All-in-One AI Framework and Toolkit Targeting Claude Code and Codex Workflows — 3.8K StarsTrellis is a Python AI framework at 3,783 stars with explicit claude-code and codex topic tags, positioning itself as a unified abstraction layer above individual coding agents. Details on its specific primitives and architecture are in the README, but its rapid star accumulation and explicit coding-agent focus distinguish it from generic LLM frameworks. Worth watching as a potential framework layer that consolidates patterns emerging from the Claude Code ecosystem.

Graph relationships

USES
Modly
Modly added TRELLIS for 3D mesh generation.
Source finding
SUPPORTS
Claude Code
Trellis is an agent harness framework supporting Claude Code and Codex workflows.
Source finding
SUPPORTS
Claude Code
Trellis AI framework targets Claude Code workflows.
Source finding
SUPPORTS
Codex
Trellis targets Codex workflows.
Source finding
SUPPORTS
Claude Code
Trellis targets Claude Code workflows.
Source finding
USES
Modly -> TRELLIS
Modly added TRELLIS for 3D mesh generation.
Source finding

Source trail

Fincept-Corporation/FinceptTerminal shivampkumar/trellis-mac thunderbird/thunderbolt Latent Space Microsoft / GitHub arXiv r/LocalLLaMA / Modly GitHub

Graph sources

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