#6969th of 70 in Open modelsFor image, video and design, image and design

star-vector

Vision-language model that converts images and text into SVG code

Stars
4.6k
License
Apache-2.0
Last commit
Nov 2025
Language
Python
Stars, last 29 weeks+300
21 Apr 2026: 4,339 stars28 Apr 2026: 4,353 stars5 May 2026: 4,364 stars12 May 2026: 4,377 stars19 May 2026: 4,393 stars26 May 2026: 4,398 stars2 Jun 2026: 4,411 stars9 Jun 2026: 4,419 stars16 Jun 2026: 4,429 stars23 Jun 2026: 4,437 stars30 Jun 2026: 4,443 stars7 Jul 2026: 4,454 stars14 Jul 2026: 4,465 stars21 Jul 2026: 4,475 stars28 Jul 2026: 4,488 stars4 Aug 2026: 4,493 stars11 Aug 2026: 4,502 stars18 Aug 2026: 4,531 stars25 Aug 2026: 4,545 stars1 Sept 2026: 4,555 stars8 Sept 2026: 4,566 stars15 Sept 2026: 4,576 stars22 Sept 2026: 4,586 stars29 Sept 2026: 4,603 stars6 Oct 2026: 4,606 stars13 Oct 2026: 4,614 stars20 Oct 2026: 4,625 stars27 Oct 2026: 4,630 stars3 Nov 2026: 4,634 stars10 Nov 2026: 4,639 stars

4,339 on 21 Apr 20264,639 on 10 Nov 2026

From GitHub's daily star counts.

Checked on GitHub.

Before you pick it

  • No commits in a year. The last commit was on 2025-11-07; fixes and security patches may not come. Source (opens in a new tab), checked .

Overview

StarVector is a multimodal model built on StarCoder that generates SVG code directly from an image (image2SVG) or a text prompt (text2SVG). The repo has inference code, 1B and 8B checkpoints on Hugging Face, training scripts (DeepSpeed for 1B, FSDP for 8B), the SVG-Stack dataset and the SVG-Bench evaluation suite. A Gradio demo runs on the HF backend or a vLLM fork.

Who it is for: Researchers and developers vectorizing icons, logos and diagrams into SVG code

Strengths

  • Outputs SVG code using primitives like ellipses, polygons and text, not only path curves
  • Ships 1B and 8B checkpoints plus SVG-Stack (2.1M train) and SVG-Bench datasets
  • Includes training and evaluation scripts, with HF and vLLM generation backends
  • 8B has the highest listed DinoScore on all five SVG-Bench sets in the README table

Weaknesses

  • Not trained on natural images or illustrations; suited to icons, logos, diagrams, charts
  • vLLM backend needs a separate StarVector fork of vLLM
  • Demo needs three processes (controller, web server, worker) started by hand
  • Reference training commands assume 8 GPUs

What it needs

  • GPU required
  • Docker
  • Needs PyTorch, Hugging Face Transformers, Gradio, vLLM fork (optional), DeepSpeed and Accelerate (training)
  • Models: starvector-1b-im2svg, starvector-8b-im2svg, Hugging Face Transformers, vLLM
  • port 7000

Quick answers

Is star-vector open source?

Yes. Its code is on GitHub under the Apache-2.0 license.

Can you run star-vector with Docker?

Yes. Its repository has a Docker setup: a Dockerfile, a Compose file or a published image.

Does star-vector need a GPU?

Yes, it needs a GPU.

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