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Gemma 4 31B vs Qwen3 VL 30B A3B Instruct

Compare Gemma 4 31B and Qwen3 VL 30B A3B Instruct side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.

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GoogleGemma 4 31B
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QwenQwen3 VL 30B A3B Instruct
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Gemma 4 31B vs Qwen3 VL 30B A3B Instruct Comparison Table

Evals updated September 22, 2026Pricing updated September 23, 2026

PropertyGemma 4 31BQwen3 VL 30B A3B Instruct
OrganizationGoogleQwen
Categoryopenopen
Modalitymultimodalmultimodal
Release DateApr 2026Oct 2025
Context Window256K262K
Parameters31B31B
LicenseApache 2.0Apache 2.0
Pricing per 1M tokens
Input $/1M$0.090$0.130
Output $/1M$0.340$0.520
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks
Overall
67.0%
Not evaluated
Quantizationsself-hosted
BF1666.9%FP867.0%QAT-W4A1667.0%hardware →
Avg cost / sample$0.0015
Avg speed / sample34.36s
By task
Object Detection
47.5%
±0.6, Mean of 3 runs, range 46.8 to 48.0
$0
Counting
51.4%
±2.7, Mean of 3 runs, range 48.6 to 54.0
$0
Identification
79.2%
±1.6, Mean of 3 runs, range 78.1 to 81.3
$0
OCR
90.8%
±0.6, Mean of 3 runs, range 90.2 to 91.5
$0
Data Extraction
80.4%
±1.0, Mean of 3 runs, range 79.4 to 81.4
$0
Reasoning
52.8%
±1.3, Mean of 3 runs, range 51.7 to 54.3
$0

Gemma 4 31B vs Qwen3 VL 30B A3B Instruct: Overview

Gemma 4 31B

Gemma 4 31B is the largest dense model in Google's Gemma 4 family, built from the same research as Gemini 3 and released as open weights under the Apache 2.0 license. It supports a 256K token context window with text and image input, configurable thinking mode for step-by-step reasoning, and multilingual support across 140+ languages. The unquantized model fits on a single 80GB GPU.

For vision tasks, Gemma 4 31B supports image understanding with variable aspect ratios and resolutions, and can output structured bounding boxes for UI element detection, making it useful for document parsing and UI understanding. Compared to Gemma 3, it delivers stronger reasoning and multimodal performance. It is part of a four-size family alongside the 26B A4B MoE variant and two on-device models (E2B, E4B), with the 31B dense variant optimized for output quality and fine-tuning over inference speed.

Qwen3 VL 30B A3B Instruct

Qwen3 VL 30B A3B Instruct is an open-weight multimodal large language model developed by Alibaba as part of the Qwen family, built for instruction-following tasks that unify text generation with visual and video understanding. Released around October 2025 under the Apache-2.0 license, it targets efficient, high-fidelity vision-language reasoning across very long contexts.

The model accepts text and image inputs and produces text outputs, with strong performance in OCR, spatial reasoning, long-video understanding, and agentic or GUI-centric visual tasks. It uses a Mixture-of-Experts (A3B) design with ~31.1B total parameters and ~3B active per token, paired with Qwen3-VL’s unified multimodal stack (including Interleaved-MRoPE and DeepStack fusion) to process text, images, and video in a single architecture. OCR support expands to 32 languages, enhancing document workflows. With a native ~262K token context window (extendable further), it stands out today for its balance of scale, efficiency, long-context support, and open accessibility in multimodal systems.

Frequently Asked Questions

Qwen3 VL 30B A3B Instruct has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.

Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.