Claude Sonnet 5 vs Qwen3.7 Plus
Compare Claude Sonnet 5 and Qwen3.7 Plus side-by-side. See how these vision models stack up in Object Detection, Open Prompt, OCR, Classification, and Image Captioning.
Compare Claude Sonnet 5 vs Qwen3.7 Plus live
Run the same image across every model that supports a task and compare their outputs side-by-side.
Detect and compare bounding boxes across models on the same image.
Upload an image
Drag and drop an image here, or click to browse
Models in this comparison
Claude Sonnet 5 vs Qwen3.7 Plus on Vision Evals
Claude Sonnet 5 scores higher on 4 of the six Vision Evals tasks.
The widest gap is Object Detection, where Qwen3.7 Plus leads 60.1% to 36.1%.
Overall, Claude Sonnet 5 averages 66.4% (#21 of 31) against 67.4% (#18 of 31) for Qwen3.7 Plus.
Qwen3.7 Plus is cheaper ($0.0008 vs $0.0064 per sample), while Claude Sonnet 5 is faster (4.8s vs 7.0s per sample).
Claude Sonnet 5 vs Qwen3.7 Plus Comparison Table
Evals updated August 20, 2026Pricing updated August 24, 2026
| Property | Claude Sonnet 5 | Qwen3.7 Plus |
|---|---|---|
| Organization | Anthropic | Qwen |
| Category | closed | closed |
| Modality | multimodal | — |
| Release Date | Jun 2026 | — |
| Context Window | 1.0M | — |
| Parameters | ||
| License | Proprietary | |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $0.320 |
| Output $/1M | $10.00 | $1.28 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | Demo |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Visual Question Answering | Demo | Demo |
| Chart Question Answering | ||
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Vision Language | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 66.4% | 67.4% |
| Avg cost / sample | $0.0064 | $0.0008 |
| Avg speed / sample | 4.84s | 7.01s |
| By task | ||
| Object Detection | 36.1% $0.011 | 60.1% $0.0013 |
| Counting | 56.8% $0.0030 | 50.0% $0.0004 |
| Identification | 81.3% $0.0027 | 84.4% $0.0003 |
| OCR | 91.7% $0.0078 | 86.5% $0.0009 |
| Data Extraction | 89.7% $0.0030 | 83.5% $0.0004 |
| Reasoning (low) | 43.0% $0.0032 | 39.7% $0.0003 |
| Reasoning (high) | 43.0% $0.0043 | 68.2% $0.0043 |
Claude Sonnet 5 vs Qwen3.7 Plus: Overview
Claude Sonnet 5 is a mid-tier large language model from Anthropic, released on June 30, 2026, as the latest model in the Sonnet series and a direct successor to Claude Sonnet 4.6. It is a hybrid reasoning model designed primarily for agentic workflows, software coding, and professional tasks. The model features a 1 million token context window, a 128k maximum output token limit, and runs adaptive thinking by default, giving API users fine-grained control over reasoning effort across five levels (low, medium, high, max, and extra-high). It uses an updated tokenizer shared with Opus 4.7 and later models, which produces approximately 30% more tokens for equivalent text compared to earlier Claude models. On benchmarks, Sonnet 5 scores 63.2% on agentic coding and 81.2% on OSWorld, narrowing the gap with Opus 4.8 while remaining at Sonnet-tier pricing.
The model supports text and image input with text output, and accepts tools including browsers and terminals for autonomous multi-step task execution. Anthropic's safety evaluations report that Sonnet 5 shows a lower rate of undesirable behaviors than Sonnet 4.6 and is generally safer in agentic contexts, with improved resistance to prompt injection and reduced sycophancy. Cybersecurity safeguards equivalent to those on Opus 4.7 and 4.8 are active, though Anthropic notes the model was not deliberately trained on cybersecurity tasks. The model is proprietary and API-only, with no open weights.
Frequently Asked Questions
On Roboflow's Vision Evals, Claude Sonnet 5 performed better. It scores higher on 4 of the six vision tasks and averages 66.4% (#21 of 31) against 67.4% (#18 of 31) for Qwen3.7 Plus. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Object Detection benchmark, Qwen3.7 Plus leads with 60.1% against 36.1%. This is the widest gap between the two models across the benchmark's tasks.
Qwen3.7 Plus is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0008 per sample against $0.0064. Claude Sonnet 5 is priced at $2.00 per 1M input tokens and $10.00 per 1M output; Qwen3.7 Plus is priced at $0.32 per 1M input tokens and $1.28 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Claude Sonnet 5 is faster. Across Roboflow's Vision Evals it averaged 4.8s per inference against 7.0s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.
Yes. The comparison demo on this page runs both models on the same image side by side for object detection and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.