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Gemma 4 12B vs Qwen3 VL 8B Instruct

We don't benchmark Gemma 4 12B or Qwen3 VL 8B Instruct on Vision Evals. Both are open-weight under Apache 2.0, so either is free for commercial use.

Compare Gemma 4 12B vs Qwen3 VL 8B Instruct live

Run the same image across every model that supports a task and compare their outputs side-by-side.

These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.

Gemma 4 12B vs Qwen3 VL 8B Instruct Comparison Table

Pricing updated November 7, 2026

PropertyGemma 4 12BQwen3 VL 8B Instruct
OrganizationGoogleQwen
Categoryopenopen
Modalitymultimodalmultimodal
Release DateJun 2026Oct 2025
Context Window—256K
Parameters12B8.8B
LicenseApache 2.0Apache 2.0
Commercial usefree for commercial usefree for commercial use
Pricing per 1M tokens
Input $/1MNo published price$0.250
Output $/1MNo published price$0.750
Vision Tasks
CaptioningSupportedDemo
OCRSupportedDemo
Visual Question AnsweringSupportedDemo
Chart Question AnsweringNot listedSupported
ClassificationNot listedSupported
Document Question AnsweringNot listedSupported
Image TaggingNot listedSupported
Multi-Label ClassificationNot listedSupported
Object DetectionNot listedSupported
Both support 1 more task
Model Features
Foundation VisionNot listedSupported
LLMs with Vision CapabilitiesNot listedSupported
Both support 1 more feature

Gemma 4 12B vs Qwen3 VL 8B Instruct: Overview

Gemma 4 12B

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

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.