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Gemini 3.1 Pro vs Qwen3.5 122B A10B

Gemini 3.1 Pro: 76.8% average across five Vision Evals tasks (#14 of 65 models). We have not run Qwen3.5 122B A10B through Roboflow's Vision Evals, so there is no head-to-head score. Run both on your own image below.

Compare Gemini 3.1 Pro vs Qwen3.5 122B A10B live

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GoogleGemini 3.1 Pro
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QwenQwen3.5 122B A10B
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Gemini 3.1 Pro vs Qwen3.5 122B A10B Comparison Table

Evals updated October 26, 2026Pricing updated November 5, 2026

PropertyGemini 3.1 ProQwen3.5 122B A10B
OrganizationGoogleQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateFeb 2026Feb 2026
Context Window1.0M256K
ParametersUnknown122B
LicenseProprietaryApache 2.0
Commercial usecommercial use per vendor termsfree for commercial use
Pricing per 1M tokens
Input $/1M$2.00$0.260
Output $/1M$12.00$2.08
Vision Tasks
ClassificationDemoSupported
Object DetectionDemoSupported
Both support 8 more tasks
Model Features
Both support 3 more features
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
76.8%
Not evaluated
Avg cost / sample$0.010–
Avg speed / sample8.44s–
By task
Object Detection
67.4%
$0.010
–
Counting
71.6%
$0.0071
–
Identification
100.0%
$0.0070
–
OCR (low)
72.6%
$0.010
–
by category
Single value
67.8%
Transcription
88.5%
Structured JSON
82.0%
Text localization
52.0%
OCR (high)
73.1%
$0.026
–
by category
Single value
68.7%
Transcription
90.8%
Structured JSON
83.9%
Text localization
47.1%
Reasoning (low)
72.2%
$0.012
–
Reasoning (high)
74.8%
$0.021
–

Gemini 3.1 Pro vs Qwen3.5 122B A10B: 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 122B A10B

Qwen3.5-122B-A10B is a high-capacity multimodal Mixture-of-Experts (MoE) model developed by Alibaba’s Qwen team as part of the Qwen3.5 model family. The architecture contains 122 billion total parameters while activating roughly 10 billion per token through sparse expert routing, allowing the model to balance large-scale reasoning ability with relatively efficient inference compared to dense models of similar size.

The model is designed to process both text and visual inputs within a unified multimodal framework, enabling tasks that require reasoning across images, documents, charts, and natural language. This makes it suitable for applications such as document understanding, diagram interpretation, and complex visual question answering.

Qwen3.5-122B-A10B supports a native context window of approximately 256,000 tokens, which can be extended further through techniques such as YaRN scaling to support very long-context workloads. Released under the Apache 2.0 license, it builds on earlier Qwen multimodal systems and provides developers with an open-weight model capable of handling demanding multimodal reasoning and analysis tasks.