Gemma 3 27B vs LLaVA-1.5
Compare Gemma 3 27B and LLaVA-1.5 side-by-side.
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Gemma 3 27B vs LLaVA-1.5: Overview
Gemma 3 27B, announced on March 12, 2025, is the largest open-weight model in Google DeepMind’s Gemma 3 family. With around 27 billion parameters, it is multimodal—accepting both text and images as input and producing text outputs. It supports a 128,000-token context window and typically generates up to ~8,192 tokens, enabling it to process multi-page documents, extended conversations, or large batches of images in a single prompt.
The model is instruction-tuned in its “-it” variants for chat, reasoning, and summarization use cases, and it supports structured outputs and function calling. It is multilingual, covering over 140 languages. Deployment is flexible: the full BF16 model requires ~46 GB of VRAM, but quantization-aware training (QAT) versions in 8-bit or 4-bit reduce the footprint significantly, allowing more accessible use outside large-scale clusters. While it delivers stronger reasoning and multimodal performance than smaller Gemma models, it remains lighter and more open than proprietary systems, making it well-suited for research, development, and fine-tuned applications.
LLaVA-1.5 is an open-source large multimodal model released in October 2023 by researchers at the University of Wisconsin-Madison and Microsoft Research. It builds on the original LLaVA architecture by introducing targeted refinements: switching the vision encoder to CLIP-ViT-L at 336-pixel resolution, replacing the projection layer with a two-layer MLP, and adding academic-task-oriented visual question answering data with response formatting prompts during training. These modifications achieve state-of-the-art performance across 11 benchmarks at release, with training completing in approximately one day on a single 8-A100 node.
The model accepts an image paired with a text prompt and generates natural language responses, supporting visual question answering, image captioning, and open-ended visual conversation. LLaVA-1.5 is available in 7B and 13B parameter variants built on the Vicuna language model, and is distributed under the Llama 2 Community License due to its Llama-2-based foundation. The original LLaVA paper was presented as an oral at NeurIPS 2023. Subsequent releases in the series (LLaVA-NeXT (LLaVA-1.6), LLaVA-NeXT-Video, and LLaVA-OneVision) are separate models with their own release pages and build on this foundation with expanded OCR, video, and multi-image capabilities.
Gemma 3 27B vs LLaVA-1.5 Comparison Table
| Property | Gemma 3 27B | LLaVA-1.5 |
|---|---|---|
| Organization | Microsoft | |
| Category | open | open |
| Modality | multimodal | multimodal |
| Release Date | Mar 2025 | Oct 2023 |
| Context Window | 128K | — |
| Parameters | 7B, 13B | |
| License | Proprietary | Custom |
| Pricing per 1M tokens | ||
| Input $/1M | $0.080 | |
| Output $/1M | $0.160 | |
| Vision Tasks | ||
| Vision Language | ||
| Visual Question Answering | Demo | |
| Captioning | Demo | |
| OCR | Demo | |
| Model Features | ||
| Multimodal Vision | ||
| LLMs with Vision Capabilities | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Overall Score | 58.21% | |
| Avg Response Time | 33.60s | |
| Defect Detection | 60%(9/15) | |
| Document Understanding | 77.8%(7/9) | |
| Object Counting | 10%(1/10) | |
| Object Understanding | 71.4%(10/14) | |
| Spatial Understanding | 63.2%(12/19) | |