Gemma 4 12B vs Qwen3 VL 8B Instruct
Compare Gemma 4 12B and Qwen3 VL 8B Instruct side-by-side.
Compare Gemma 4 12B vs Qwen3 VL 8B Instruct live
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Models in this comparison
Gemma 4 12B vs Qwen3 VL 8B Instruct: Overview
Gemma 4 12B is an open-weight multimodal model from Google in the Gemma 4 family. It is intended for text and image understanding tasks such as visual question answering, OCR, captioning, and document understanding, with a smaller parameter footprint than the larger Gemma 4 variants.
This entry is connected to Roboflow Playground vision evals for comparison. No runnable Playground workflow is configured yet, so the model page is used for discovery and benchmark context rather than direct hosted inference.
Qwen3 VL 8B Instruct is an open-weight multimodal vision-language model developed by Qwen / Alibaba Cloud as part of the Qwen3-VL series, designed for instruction-following tasks that combine text with visual inputs such as images and video. Released around October 2025 under the Apache-2.0 license, it targets developers who need capable multimodal reasoning without the scale or cost of very large models.
The model contains roughly 8.8 billion dense parameters and supports text, image, and video understanding with strong spatial perception, visual reasoning, and emerging visual agent abilities such as GUI interaction. A standout feature is its native ~256K token context window, extendable to around 1M tokens, enabling long-document reading and extended video comprehension. In today’s landscape, it balances openness, long-context capacity, and solid multimodal performance against heavier proprietary models. Typical applications include multimodal assistants, document and video analysis, visual question answering, and research or product prototyping where transparency and deployability matter.
Gemma 4 12B vs Qwen3 VL 8B Instruct Comparison Table
| Property | Gemma 4 12B | Qwen3 VL 8B Instruct |
|---|---|---|
| Organization | Qwen | |
| Category | open | open |
| Modality | multimodal | multimodal |
| Release Date | Jun 2026 | Oct 2025 |
| Context Window | — | 256K |
| Parameters | 12B | 8.8B |
| License | Apache 2.0 | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $0.080 | |
| Output $/1M | $0.500 | |
| Vision Tasks | ||
| Captioning | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Object Detection | ||
| Model Features | ||
| Multimodal Vision | ||
| LLMs with Vision Capabilities | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Overall Score | 62.69% | |
| Avg Response Time | 6.88s | |
| Defect Detection | 73.3%(11/15) | |
| Document Understanding | 88.9%(8/9) | |
| Object Counting | 10%(1/10) | |
| Object Understanding | 78.6%(11/14) | |
| Spatial Understanding | 57.9%(11/19) | |