Claude Opus 4.8 vs Claude Opus 5.5
Compare Claude Opus 4.8 and Claude Opus 5.5 side-by-side. See how these vision models stack up in Image Captioning, Classification, OCR, Object Detection, and Open Prompt.
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Models in this comparison
Claude Opus 4.8 vs Claude Opus 5.5 on Vision Evals
Claude Opus 5.5 scores higher on all five Vision Evals tasks.
The widest gap is Object Detection, where Claude Opus 5.5 leads 74.5% to 38.6%.
Overall, Claude Opus 4.8 averages 58.3% (#38 of 63) against 82.0% (#3 of 63) for Claude Opus 5.5.
Claude Opus 5.5 is both cheaper ($0.015 vs $0.021 per sample) and faster (7.6s vs 7.7s per sample).
Claude Opus 4.8 vs Claude Opus 5.5 Comparison Table
Evals updated October 13, 2026Pricing updated October 17, 2026
| Property | Claude Opus 4.8 | Claude Opus 5.5 |
|---|---|---|
| Organization | Anthropic | Anthropic |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | May 2026 | Sep 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | Unknown | Unknown |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | $4.00 |
| Output $/1M | $25.00 | $20.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | Supported | Supported |
| Classification | Demo | Demo |
| Document Question Answering | Supported | Supported |
| Image Tagging | Supported | Supported |
| Multi-Label Classification | Supported | Supported |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | Supported | Supported |
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | Supported | Supported |
| LLMs with Vision Capabilities | Supported | Supported |
| Multimodal Vision | Supported | Supported |
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 58.3% | 82.0% |
| Avg cost / sample | $0.021 | $0.015 |
| Avg speed / sample | 7.66s | 7.63s |
| By task | ||
| Object Detection (low) | 38.6% | 74.5% ±0.5, Mean of 3 runs, range 74.0 to 75.0 |
| Object Detection (high) | – | 76.0% ±1.1, Mean of 3 runs, range 74.7 to 77.0 |
| Counting (low) | 54.0% | 80.6% ±2.0, Mean of 3 runs, range 78.4 to 82.4 |
| Counting (high) | – | 82.0% ±2.0, Mean of 3 runs, range 79.7 to 83.8 |
| Identification (low) | 84.4% | 93.8% ±0.0, Mean of 3 runs, range 93.8 to 93.8 |
| Identification (high) | – | 95.8% ±1.6, Mean of 3 runs, range 93.8 to 96.9 |
| OCR (low) | 61.5% | 78.3% |
| by category |
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| OCR (high) | 62.1% | 79.9% |
| by category |
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| Reasoning (low) | 53.0% | 83.0% ±1.0, Mean of 3 runs, range 82.1 to 84.1 |
| Reasoning (high) | 52.3% | 85.9% ±2.6, Mean of 3 runs, range 82.8 to 88.1 |
Claude Opus 4.8 vs Claude Opus 5.5: Overview
Claude Opus 4.8 is Anthropic's most capable generally available large language model, released on May 28, 2026 as an incremental upgrade to Claude Opus 4.7. The model accepts text and image inputs and produces text outputs, with a 1 million token context window on the Claude API, Amazon Bedrock, and Google Cloud Vertex AI (200k tokens on Microsoft Foundry) and up to 128k max output tokens. It uses adaptive thinking and supports adjustable effort tiers — high by default, with extra and max tiers available for more demanding tasks. A fast mode operates at approximately 2.5x standard speed. The model is described by Anthropic as a hybrid reasoning model designed for advanced coding, agentic workflows, long-context reasoning, and professional knowledge work.
Key behavioral improvements over Opus 4.7 include substantially reduced rates of unreported code flaws, improved honesty in self-assessment, and better tool-calling reliability. On Anthropic's Super-Agent benchmark, Opus 4.8 completes every case end-to-end, and it scores 84% on Online-Mind2Web for computer-use and browser-agent tasks. It achieves 88.6% on SWE-bench Verified and 69.2% on SWE-bench Pro. Alongside the model, Anthropic launched Dynamic Workflows in Claude Code (research preview), which enables Claude to orchestrate hundreds of parallel subagents for codebase-scale tasks such as large migrations. The Messages API was also updated to accept mid-task system messages without breaking prompt caching, improving support for long-running agentic pipelines.
Claude Opus 5.5 is a proprietary multimodal reasoning model from Anthropic and the first entry in the Claude 5.5 family. It accepts interleaved text and image input and returns text, with a one million token context window and up to 128,000 output tokens per response. Adaptive thinking is always enabled on this model and cannot be disabled; thinking depth is instead governed by an effort parameter with five levels, where medium is the default, a change from the high default used by Claude Opus 5 and earlier Opus models. Anthropic reports a knowledge cutoff of June 2026.
On the visual side, Anthropic characterizes Opus 5.5 as its strongest Opus release for vision and computer use, describing improved reading of dense documents, charts, screenshots, and diagrams for document extraction and visual analysis tasks. Published results include 89.0% on Chartography with tools and 81.8% on OSWorld 2.0 under partial credit scoring, alongside 48.7% under strict scoring reported in the system card. The accompanying system card states that Opus 5.5 scored higher than Opus 5 on every evaluation in its capability summary, with the largest gains concentrated in agentic coding, visual reasoning, computer use, and long-horizon knowledge work. The model ships with safety classifiers covering biology and cybersecurity that can route blocked requests to earlier Claude models.
Frequently Asked Questions
On Roboflow's Vision Evals, Claude Opus 5.5 performed better. It scores higher on all five vision tasks and averages 82.0% (#3 of 63) against 58.3% (#38 of 63) for Claude Opus 4.8. 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 Opus 5.5 leads with 74.5% against 38.6%. This is the widest gap between the two models across the benchmark's tasks.
Claude Opus 5.5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.015 per sample against $0.021. Claude Opus 4.8 is priced at $5.00 per 1M input tokens and $25.00 per 1M output; Claude Opus 5.5 is priced at $4.00 per 1M input tokens and $20.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Claude Opus 5.5 is faster. Across Roboflow's Vision Evals it averaged 7.6s per inference against 7.7s. 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 image captioning and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.