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Gemma 4 26B A4B vs Qwen-VL

Compare Gemma 4 26B A4B and Qwen-VL side-by-side.

Compare Gemma 4 26B A4B vs Qwen-VL live

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

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Gemma 4 26B A4B vs Qwen-VL Comparison Table

Evals updated July 24, 2026Pricing updated July 25, 2026

PropertyGemma 4 26B A4BQwen-VL
OrganizationGoogleQwen
Categoryopenopen
Modalitymultimodalmultimodal
Release DateApr 2026Aug 2023
Context Window256K
Parameters25.2B
LicenseApache 2.0Custom
Pricing per 1M tokens
Input $/1M$0.120
Output $/1M$0.350
Vision Tasks
CaptioningDemo
Vision Language
Visual Question AnsweringDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemo
OCRDemo
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision

Gemma 4 26B A4B vs Qwen-VL: Overview

Gemma 4 26B A4B

Gemma 4 26B A4B is the Mixture-of-Experts variant in Google's Gemma 4 family, with 25.2B total parameters but only 3.8B active per token. Built from the same Gemini 3 research as the 31B dense sibling and released as open weights under the Apache 2.0 license, it supports a 256K token context window with text and image input and configurable thinking mode. The "A4B" in the name refers to its approximately 4B active parameters. The MoE design makes it significantly faster at inference than the dense 31B, running nearly as fast as a 4B-parameter model while delivering roughly 97% of the dense model's quality.

For vision tasks, the 26B A4B shares the same multimodal capabilities as the 31B image understanding with variable aspect ratios and resolutions, and structured bounding box output for UI element detection. The tradeoff versus the 31B dense model is a small quality reduction in exchange for much faster inference and lower hardware requirements, fitting in 18GB of VRAM at 4-bit quantization. It ranked #6 among open models on the Arena AI text leaderboard at launch.

Qwen-VL

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.