Gemma 3 27B vs Qwen-VL
Compare Gemma 3 27B and Qwen-VL side-by-side.
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Gemma 3 27B vs Qwen-VL: 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.
Qwen-VL is a large vision-language model released in August 2023 by the Qwen team at Alibaba Cloud. Built on the 7-billion-parameter Qwen language model with an added visual receptor based on Openclip ViT-bigG, the model accepts images, text, and bounding box coordinates as inputs, and can produce both text and bounding boxes as outputs. Qwen-VL processes images at 448×448 resolution, higher than the 224×224 input used by many contemporaneous vision-language models, which supports finer-grained visual recognition and text-heavy tasks such as OCR. This design supports a range of multimodal tasks in a single model, including image captioning, visual question answering, visual grounding, text recognition, and image-conditioned dialogue, with native support for English, Chinese, and multilingual conversation.
At release, Qwen-VL achieved competitive results against contemporaneous vision-language models across zero-shot captioning, general VQA, text-oriented VQA, and referring expression comprehension benchmarks. A chat-tuned variant, Qwen-VL-Chat, is optimized for interactive use with instruction-following and multi-turn conversation. The model is distributed under the Tongyi Qianwen License, a custom license from Alibaba Cloud with specific terms that should be reviewed prior to commercial use. Qwen-VL is the first generation of Alibaba's open multimodal series and precedes the later Qwen2-VL and Qwen2.5-VL releases.
Gemma 3 27B vs Qwen-VL Comparison Table
| Property | Gemma 3 27B | Qwen-VL |
|---|---|---|
| Organization | Qwen | |
| Category | open | open |
| Modality | multimodal | multimodal |
| Release Date | Mar 2025 | Aug 2023 |
| Context Window | 128K | — |
| Parameters | ||
| License | Proprietary | Custom |
| Pricing per 1M tokens | ||
| Input $/1M | $0.080 | |
| Output $/1M | $0.160 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Vision Language | ||
| Visual Question Answering | 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) | |