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Claude Opus 4 vs Qwen3.5 397B A17B

We don't benchmark Claude Opus 4 or Qwen3.5 397B A17B on Vision Evals. Claude Opus 4 is proprietary under Proprietary: commercial use per vendor terms. Qwen3.5 397B A17B is open-weight under Apache 2.0: free for commercial use.

Anthropic

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AnthropicClaude Opus 4

Claude Opus 4 is deprecated and can no longer be run. Details and evals are still available on its model page.

QwenQwen3.5 397B A17B
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Claude Opus 4 vs Qwen3.5 397B A17B Comparison Table

Pricing updated November 10, 2026

PropertyClaude Opus 4Qwen3.5 397B A17B
OrganizationAnthropicQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateMay 2025Feb 2026
Context Window200K262K
ParametersUnknown397B
LicenseProprietaryApache 2.0
Commercial usecommercial use per vendor termsfree for commercial use
Pricing per 1M tokens
Input $/1MNo published price$0.600
Output $/1MNo published price$3.60
Vision Tasks
CaptioningSupportedDemo
OCRSupportedDemo
Visual Question AnsweringSupportedDemo
Both support 7 more tasks
Model Features
Both support 3 more features

Claude Opus 4 vs Qwen3.5 397B A17B: Overview

Claude Opus 4

Claude 4 Opus, released by Anthropic in May 2025, is the flagship model of the Claude 4 family, built for complex, long-horizon reasoning and advanced coding workflows. It is multimodal, supporting text (including voice), images, and tool use, and operates as a hybrid reasoning model—able to deliver quick answers in fast mode or switch to extended thinking for deeper, multi-step problem solving. With a ~200,000-token context window and a training cutoff around March 2025, it is optimized for handling large documents, long conversations, and sophisticated agentic tasks.

It is best suited for research, enterprise automation, and software development at scale. The model is classified at Anthropic’s ASL-3 safety level, denoting advanced oversight and safety features.

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.