Claude Opus 5 vs Claude Sonnet 5.5
Compare Claude Opus 5 and Claude Sonnet 5.5 side-by-side.
Compare Claude Opus 5 vs Claude Sonnet 5.5 live
Run the same image across every model that supports a task and compare their outputs side-by-side.
These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Models in this comparison
Claude Opus 5 vs Claude Sonnet 5.5 on Vision Evals
Claude Sonnet 5.5 scores higher on 5 of the six Vision Evals tasks.
The widest gap is Object Detection, where Claude Sonnet 5.5 leads 74.3% to 54.4%.
Overall, Claude Opus 5 averages 78.3% (#17 of 60) against 83.8% (#7 of 60) for Claude Sonnet 5.5.
Claude Sonnet 5.5 is cheaper ($0.0065 vs $0.017 per sample), while Claude Opus 5 is faster (7.4s vs 10.8s per sample).
Claude Opus 5 vs Claude Sonnet 5.5 Comparison Table
Evals updated September 28, 2026Pricing updated September 28, 2026
| Property | Claude Opus 5 | Claude Sonnet 5.5 |
|---|---|---|
| Organization | Anthropic | Anthropic |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jul 2026 | Sep 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | |
| Output $/1M | $25.00 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Multi-Label Classification | ||
| Object Detection | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Image Tagging | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 78.3% | 83.8% |
| Avg cost / sample | $0.017 | $0.0065 |
| Avg speed / sample | 7.38s | 10.78s |
| By task | ||
| Object Detection (low) | 54.4% | 74.3% ±0.9, Mean of 3 runs, range 73.5 to 75.3 |
| Object Detection (high) | – | 76.8% ±0.4, Mean of 3 runs, range 76.5 to 77.3 |
| Counting (low) | 70.3% | 79.3% ±0.7, Mean of 3 runs, range 78.4 to 79.7 |
| Counting (high) | – | 82.9% ±1.4, Mean of 3 runs, range 81.1 to 83.8 |
| Identification (low) | 90.6% | 91.7% ±3.1, Mean of 3 runs, range 87.5 to 93.8 |
| Identification (high) | – | 90.6% ±0.0, Mean of 3 runs, range 90.6 to 90.6 |
| OCR (low) | 93.2% | 90.6% ±0.9, Mean of 3 runs, range 90.0 to 91.7 |
| OCR (high) | – | 90.9% ±1.5, Mean of 3 runs, range 89.2 to 92.3 |
| Data Extraction (low) | 89.7% | 90.7% ±1.5, Mean of 3 runs, range 89.7 to 92.8 |
| Data Extraction (high) | – | 93.1% ±0.5, Mean of 3 runs, range 92.8 to 93.8 |
| Reasoning (low) | 71.5% | 76.4% ±0.7, Mean of 3 runs, range 75.5 to 76.8 |
| Reasoning (high) | 74.2% | 83.9% ±1.7, Mean of 3 runs, range 82.1 to 85.4 |
Claude Opus 5 vs Claude Sonnet 5.5: Overview
Claude Opus 5 is a large language model with multimodal vision capabilities developed by Anthropic, released on July 24, 2026 as the fourth model in the Claude 5 family. It sits in the Opus tier of Anthropic's lineup, positioned below the Mythos-class Fable 5 and Mythos 5 models, and is framed by Anthropic as the go-to model for most knowledge work and automation tasks. The model approaches Fable 5's capabilities at roughly half the cost, priced at $5 per million input tokens and $25 per million output tokens. It becomes the default model on Claude Max and the strongest model available on Claude Pro. The model ships with a 1 million token context window and an adjustable "effort" parameter that allows users to trade reasoning depth for speed and token savings. Early enterprise customers reported that Opus 5 achieved comparable performance to Opus 4.8's maximum-reasoning mode while generating significantly fewer tokens on average, and demonstrated higher accuracy on financial modeling tasks with fewer tool calls and less time.
Claude Opus 5 supports multimodal inputs including images and text, and is designed for agentic workflows, coding, scientific research, and complex enterprise tasks. Anthropic reports the model scores 10.2 percentage points higher than Opus 4.8 on an internal chemistry benchmark, making it the most capable generally available model for scientific research in the Claude lineup. Cyber classifiers on Opus 5 are designed to intervene approximately 85 percent less often than those on Fable 5, with fallback to Opus 4.8 when a classifier triggers. The model does not retain user data for 30 days, unlike Fable 5. It is available across Anthropic's platforms including Claude Code and Claude Cowork, as well as cloud partners.
Claude Sonnet 5.5 is a proprietary multimodal language model from Anthropic and the second release in the Claude 5.5 family, following Claude Opus 5.5. It accepts interleaved text and image input and returns text, operating with a 1M token context window and a maximum output of 128K tokens per request. The model uses adaptive thinking by default, allocating variable reasoning effort per request rather than exposing a manual extended thinking toggle, and its training data cutoff is June 2026. Anthropic positions it as a faster, lower cost complement to Opus 5.5 for well scoped everyday tasks, bug fixing, and producing documents, slides, and spreadsheets.
On visual and agentic evaluations reported at launch, Sonnet 5.5 scores 61.6% on Chartography, a chart recognition test, compared with 15.6% for Claude Sonnet 5, and 80.1% on OSWorld 2.1, a computer use benchmark measuring screenshot driven control of a desktop environment, compared with 57.0% for Sonnet 5. It reports 70.6% on Terminal-Bench 4.0 for agentic coding. Anthropic describes it as the first Sonnet model able to complete Pokemon Red from screenshots alone, and it generates output more than 30% faster than Sonnet 5 while using fewer tokens for equivalent work.
Frequently Asked Questions
On Roboflow's Vision Evals, Claude Sonnet 5.5 performed better. It scores higher on 5 of the six vision tasks and averages 83.8% (#7 of 60) against 78.3% (#17 of 60) for Claude Opus 5. 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 at low effort, Claude Sonnet 5.5 leads with 74.3% against 54.4%. This is the widest gap between the two models across the benchmark's tasks.
Claude Sonnet 5.5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0065 per sample against $0.017. Actual costs depend on your image sizes, prompts, and output length.
Claude Opus 5 is faster. Across Roboflow's Vision Evals it averaged 7.4s per inference against 10.8s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.