Claude Opus 4.1 vs Qwen3.5 122B A10B

Compare Claude Opus 4.1 and Qwen3.5 122B A10B side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.

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AnthropicClaude Opus 4.1
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QwenQwen3.5 122B A10B
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Claude Opus 4.1 vs Qwen3.5 122B A10B: Overview

Claude Opus 4.1

Claude 4.1 Opus, released by Anthropic in August 2025, is the upgraded flagship of the Claude 4 family, building on Opus 4 with stronger reasoning and agentic capabilities. Like its predecessor, it is multimodal and optimized for text, code, and tool use, with support for large context windows suited to multi-file codebases, technical workflows, and long-horizon problem solving.

On benchmarks, Opus 4.1 improves coding performance, reaching ~74.5% on SWE-Bench Verified compared to Opus 4’s ~72.5%. It demonstrates more precise debugging, refactoring, and orchestration of agentic tasks while maintaining similar safety and alignment safeguards. It is best suited for enterprise-scale software development, research automation, and advanced reasoning workflows where reliability and depth of analysis are critical.

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.

Claude Opus 4.1 vs Qwen3.5 122B A10B Comparison Table

PropertyClaude Opus 4.1Qwen3.5 122B A10B
OrganizationAnthropicQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateAug 2025Feb 2026
Context Window200K256K
Parameters122B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$15.00$0.260
Output $/1M$75.00$2.08
Vision Tasks
CaptioningDemoDemo
Object DetectionDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
ClassificationDemo
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Visual Understanding
Overall Score
59.7%
76.12%
Avg Response Time7.09s1.77s
Median input tokensincl. image tokens2.0K1.2K
Median output tokens1407
Est. cost / taskon this benchmark$0.040$0.0003
Defect Detection
73.3%(11/15)
86.7%(13/15)
Document Understanding
88.9%(8/9)
77.8%(7/9)
Object Counting
0%(0/10)
40%(4/10)
Object Understanding
64.3%(9/14)
92.9%(13/14)
Spatial Understanding
63.2%(12/19)
73.7%(14/19)
OCR
Overall Score
68.56%
Avg Response Time5.08s
Median input tokensincl. image tokens552
Median output tokens97
Est. cost / taskon this benchmark$0.016
Focused Scene OCR
73.7%(73/99)
Handwritten Math
30%(3/10)
License Plate Recognition
53.3%(16/30)
Text Recognition
80%(24/30)
VQA & Extraction
68.3%(41/60)

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