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.
Upload an image
Drag and drop an image here, or click to browse
Models in this comparison
Claude Opus 4.1 vs Qwen3.5 397B A17B: Overview
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 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
| Property | Claude Opus 4.1 | Qwen3.5 397B A17B |
|---|---|---|
| Organization | Anthropic | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Aug 2025 | Feb 2026 |
| Context Window | 200K | 262K |
| Parameters | 397B | |
| License | Proprietary | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $15.00 | $0.385 |
| Output $/1M | $75.00 | $2.45 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Object Detection | Demo | |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Classification | Demo | |
| 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 Time | 7.09s | 56.61s |
| Median input tokensincl. image tokens | 2.0K | 1.1K |
| Median output tokens | 140 | 54 |
| 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