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Open weightsUniversity of Wisconsin-Madison / Microsoft/10 trustVerified
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LLaVA-1.5

The foundational open vision-language baseline: CLIP + MLP + Vicuna.

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About

LLaVA-1.5, released October 5, 2023 by researchers at UW-Madison and Microsoft, is the open multimodal model that defined the vision-language baseline recipe. It pairs a CLIP ViT-L/14 vision encoder with a Vicuna language model through a two-layer MLP projector, adds academic visual-QA data to the training mix, and reportedly reached state-of-the-art results across 11 multimodal benchmarks — all trained in about a day on a single 8-GPU node.

It is genuinely open under Apache 2.0, which is why it became the backbone of hundreds of derivative vision models and the foundation for the LLaVA-NeXT line. Limitations are those of its era: 336px image resolution, single-image reasoning, and far weaker OCR and instruction-following than current VLMs.

Specs

Context window

Pricing

Free quota

API access

Weights

Open weights

Released

October 5, 2023

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

visual-question-answeringimage-captioningmultimodal-researchocr

Trust score — 9/10

/10 trustVerified

Scored 9/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 72; Trending score 92/100 from researcher assessment.

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Sources