Gemma 3 4B vs Qwen3.6 Plus

Compare Gemma 3 4B and Qwen3.6 Plus side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.

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GoogleGemma 3 4B
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QwenQwen3.6 Plus
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Models in this comparison

Gemma 3 4B vs Qwen3.6 Plus: Overview

Gemma 3 4B

Gemma 3 4B, released on March 12, 2025, is the mid-sized member of Google DeepMind’s open-weight Gemma 3 family. With about 4 billion parameters, it is multimodal—supporting text and image inputs and generating text outputs. Like the larger Gemma 3 models, it features a 128,000-token input context window with an output capacity of ~8,192 tokens, enabling it to handle long documents and mixed text–image reasoning tasks.

The 4B variant is designed as a balance between efficiency and capability: it offers multilingual support across 140+ languages, strong summarization and reasoning performance, and compatibility with moderate hardware. Inference can run with ~6.4 GB VRAM in BF16, or significantly less in quantized 8-bit (~4.4 GB) or 4-bit (~3.4 GB) modes, making it accessible to developers outside large-scale infrastructure. While it lags behind the 12B and 27B versions on the most complex reasoning and multimodal benchmarks, its lower compute footprint makes it ideal for research, prototyping, and practical deployment where efficiency matters.

Qwen3.6 Plus

Qwen3.6 Plus is a flagship model in Alibaba’s Qwen Plus series, designed for agentic workflows, coding, and multi-step reasoning. It supports a 1 million token context window and up to 65,536 output tokens, with built-in reasoning capabilities. The model is available as a hosted, proprietary API through Alibaba Cloud.

Compared to Qwen3.5, it improves reliability in multi-step execution and frontend code generation, with stronger performance on agentic coding tasks. It also supports document and image understanding, though its vision capabilities are more limited than dedicated Qwen-VL models. Qwen3.6 Plus is part of a broader Qwen ecosystem that includes both closed-source APIs and open-weight models.

Gemma 3 4B vs Qwen3.6 Plus Comparison Table

PropertyGemma 3 4BQwen3.6 Plus
OrganizationGoogleQwen
Categoryopenclosed
Modalitymultimodalmultimodal
Release DateMar 2025Apr 2026
Context Window128K1.0M
Parameters4B
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.050$0.325
Output $/1M$0.100$1.95
Vision Tasks
CaptioningDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Object Detection
Model Features
Multimodal Vision
LLMs with Vision Capabilities
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Overall Score
37.31%
68.66%
Avg Response Time16.80s34.17s
Median input tokensincl. image tokens1.2K
Median output tokens47
Est. cost / taskon this benchmark$0.0005
Defect Detection
60%(9/15)
86.7%(13/15)
Document Understanding
55.6%(5/9)
77.8%(7/9)
Object Counting
0%(0/10)
20%(2/10)
Object Understanding
42.9%(6/14)
78.6%(11/14)
Spatial Understanding
26.3%(5/19)
68.4%(13/19)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology