bytedance/Lance

Health v2 · maintenance only

Flags: no_releases young

Adoption not part of the score

1329 stars · 95 forks observed · 2026-08-28

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

Lance is a 3B-parameter native unified multimodal model from ByteDance for image and video understanding, generation, and editing, trained from scratch with a multi-task synergy recipe. It is released as a research artifact with inference and fine-tuning code, model checkpoints on Hugging Face, and vLLM-Omni support.

Use cases

• generate videos from text prompts
• generate images from text descriptions
• edit images and videos with natural language instructions
• understand and reason about image and video content
• fine-tune a small unified multimodal model on custom data
• run multimodal generation on a limited GPU budget

When to choose

• you need a single compact model handling image/video understanding, generation, and editing
• you want a research baseline for unified multimodal modeling under constrained compute
• you want to experiment with fine-tuning a 3B multimodal model

When to avoid

• you need production-grade, polished output quality for commercial media generation
• you need high-resolution or high-framerate video (training capped at 768x768 images and 480p 12 FPS video)
• you only need a specialized single-task model like pure text-to-image

Facets

library · maturity active

machine-learning deep-learning image-processing video-processing llm-inference artificial-intelligence machine-learning computer-vision image-processing python multimodal-model unified-model text-to-video text-to-image image-editing video-editing research-project bytedance 3b-parameters video gpu linux

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For agents

markdown · JSON · MCP: product_card(name="bytedance/Lance")