FoundationVision/LlamaGen

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1966 stars · 95 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LlamaGen is a family of autoregressive image generation models that apply next-token prediction, as in Llama-style LLMs, to visual generation. The repo provides PyTorch training/sampling code, image tokenizers, and pre-trained class- and text-conditional models from 100M to 3B parameters, with vLLM serving support.

Use cases

• generate images from text prompts
• class-conditional image generation on ImageNet
• train an autoregressive text-to-image model
• speed up image generation inference with vLLM
• research next-token prediction for visual generation
• compare autoregressive models against diffusion models

When to choose

• you want to experiment with autoregressive image generation instead of diffusion
• you need pre-trained image generation models with open weights
• you are researching scalable visual token prediction

When to avoid

• you need a production-ready text-to-image service with broad ecosystem support
• you lack GPU resources for large model inference
• you want actively developed tooling with frequent updates

Facets

library · maturity maintenance

machine-learning deep-learning image-processing llm-inference deep-learning computer-vision image-processing artificial-intelligence python autoregressive-model text-to-image vq-vae image-tokenizer pytorch diffusion-alternative vllm pretrained-models gpu

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