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Gemini 3.1 Pro vs Qwen3.5 397B A17B

Compare Gemini 3.1 Pro and Qwen3.5 397B A17B side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, and OCR.

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GoogleGemini 3.1 Pro
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QwenQwen3.5 397B A17B
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Gemini 3.1 Pro vs Qwen3.5 397B A17B Comparison Table

Evals updated September 3, 2026Pricing updated September 4, 2026

PropertyGemini 3.1 ProQwen3.5 397B A17B
OrganizationGoogleQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateFeb 2026Feb 2026
Context Window1.0M262K
Parameters397B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$2.00$0.550
Output $/1M$12.00$3.50
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, pooled at low effort
Overall
83.3%
Not evaluated
Avg cost / sample$0.0093
Avg speed / sample7.81s
By task
Object Detection
67.4%
$0.010
Counting
71.6%
$0.0071
Identification
100.0%
$0.0070
OCR
92.6%
$0.0066
Data Extraction
95.9%
$0.0063
Reasoning (low)
72.2%
$0.012
Reasoning (high)
74.8%
$0.021

Gemini 3.1 Pro vs Qwen3.5 397B A17B: Overview

Gemini 3.1 Pro

Gemini 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.

The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.

Qwen3.5 397B A17B

Qwen3.5-397B-A17B is a 397B-parameter (17B active) open-weight multimodal model developed by Alibaba’s Qwen team, released on 2026-02-16 under Apache-2.0. It supports text and image inputs with text outputs, combining a sparse Mixture-of-Experts architecture with Gated Delta Networks for efficient scaling. The model provides native vision-language reasoning and a large ~262K token context window, extendable to ~1M tokens.

As the first open-weight release in the Qwen3.5 family, it positions itself as a high-capacity, long-context alternative in the large vision-language space, balancing scale and efficiency via sparse activation. It is designed for advanced reasoning, coding, agent workflows, and multimodal understanding tasks.