Claude Opus 4.1 vs Qwen3.5 397B A17B

Compare Claude Opus 4.1 and Qwen3.5 397B A17B side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.

Compare Claude Opus 4.1 vs Qwen3.5 397B A17B live

Run the same image across every model that supports a task and compare their outputs side-by-side.

Extract and compare text from images across multiple models.

Open OCR in the full playground
AnthropicClaude Opus 4.1
Run to compare this model.
QwenQwen3.5 397B A17B
Run to compare this model.

Models in this comparison

Claude Opus 4.1 vs Qwen3.5 397B A17B: 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 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.

Claude Opus 4.1 vs Qwen3.5 397B A17B Comparison Table

PropertyClaude Opus 4.1Qwen3.5 397B A17B
OrganizationAnthropicQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateAug 2025Feb 2026
Context Window200K262K
Parameters397B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$15.00$0.385
Output $/1M$75.00$2.45
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%
Overall Score
59.7%
58.21%
Avg Response Time7.09s56.61s
Median input tokensincl. image tokens2.0K1.1K
Median output tokens14054
Est. cost / taskon this benchmark$0.040$0.0006
Defect Detection
73.3%(11/15)
66.7%(10/15)
Document Understanding
88.9%(8/9)
77.8%(7/9)
Object Counting
0%(0/10)
20%(2/10)
Object Understanding
64.3%(9/14)
64.3%(9/14)
Spatial Understanding
63.2%(12/19)
57.9%(11/19)

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