Claude Sonnet 4.5 vs Qwen3.5 397B A17B
Compare Claude Sonnet 4.5 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 Sonnet 4.5 vs Qwen3.5 397B A17B: Overview
Claude Sonnet 4.5, released by Anthropic in September 2025, is the company’s most advanced Sonnet-series model, built for high-performance reasoning, coding, and long-horizon agentic workflows. It is a multimodal system that accepts both text and images, with a 200,000-token context window designed for handling large documents and extended interactions. Anthropic highlights its improvements in reliability, reduced sycophancy, and alignment, making it suitable for sustained enterprise use.
The model delivers strong results in coding and autonomous workflows, achieving 61.4% on the OSWorld benchmark and leading performance on SWE-bench Verified. It introduces infrastructure features such as a memory tool (beta), checkpointing for Claude Code, parallel tool use, and tighter integration with VS Code. Compared to Opus, which targets broader reasoning, Sonnet 4.5 is optimized for structured, long-duration tasks. Positioned against leading offerings from OpenAI and Google, it is aimed at enterprise automation, software engineering, and research-intensive applications.
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 Sonnet 4.5 vs Qwen3.5 397B A17B Comparison Table
| Property | Claude Sonnet 4.5 | Qwen3.5 397B A17B |
|---|---|---|
| Organization | Anthropic | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Sep 2025 | Feb 2026 |
| Context Window | 200K | 262K |
| Parameters | 397B | |
| License | Proprietary | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $3.00 | $0.385 |
| Output $/1M | $15.00 | $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% | ||
| Visual Understanding | ||
| Overall Score | 59.7% | 58.21% |
| Avg Response Time | 5.67s | 56.61s |
| Median input tokensincl. image tokens | 2.2K | 1.1K |
| Median output tokens | 182 | 54 |
| Est. cost / taskon this benchmark | $0.0092 | $0.0006 |
| Defect Detection | 73.3%(11/15) | 66.7%(10/15) |
| Document Understanding | 77.8%(7/9) | 77.8%(7/9) |
| Object Counting | 10%(1/10) | 20%(2/10) |
| Object Understanding | 64.3%(9/14) | 64.3%(9/14) |
| Spatial Understanding | 63.2%(12/19) | 57.9%(11/19) |
| OCR | ||
| Overall Score | 67.25% | 68.56% |
| Avg Response Time | 3.93s | 7.45s |
| Median input tokensincl. image tokens | 735 | 122 |
| Median output tokens | 115 | 20 |
| Est. cost / taskon this benchmark | $0.0039 | $0.0001 |
| Focused Scene OCR | 71.7%(71/99) | 57.6%(57/99) |
| Handwritten Math | 20%(2/10) | 80%(8/10) |
| License Plate Recognition | 53.3%(16/30) | 100%(30/30) |
| Text Recognition | 66.7%(20/30) | 70%(21/30) |
| VQA & Extraction | 75%(45/60) | 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