Claude Opus 4 vs Qwen3.5 397B A17B
Compare Claude Opus 4 and Qwen3.5 397B A17B side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.
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Claude Opus 4 is deprecated and can no longer be run. Details and evals are still available on its model page.
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Claude Opus 4 vs Qwen3.5 397B A17B: Overview
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.
Positioned at the high end of Anthropic’s offerings, Opus 4 achieves state-of-the-art results on coding benchmarks like SWE-Bench (72.5%) and Terminal-Bench (43.2%). 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 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 vs Qwen3.5 397B A17B Comparison Table
| Property | Claude Opus 4 | Qwen3.5 397B A17B |
|---|---|---|
| Organization | Anthropic | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | May 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 | |
| Object Detection | ||
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Classification | ||
| 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 | 56.72% | 58.21% |
| Avg Response Time | 19.74s | 56.61s |
| Median input tokensincl. image tokens | 1.1K | |
| Median output tokens | 54 | |
| Est. cost / taskon this benchmark | $0.0006 | |
| Defect Detection | 66.7%(10/15) | 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 | 57.9%(11/19) | 57.9%(11/19) |
| OCR | ||
| Overall Score | 68.56% | |
| Avg Response Time | 7.45s | |
| Median input tokensincl. image tokens | 122 | |
| Median output tokens | 20 | |
| Est. cost / taskon this benchmark | $0.0001 | |
| Focused Scene OCR | 57.6%(57/99) | |
| Handwritten Math | 80%(8/10) | |
| License Plate Recognition | 100%(30/30) | |
| Text Recognition | 70%(21/30) | |
| 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