Roboflow

Claude Opus 5 vs Claude Opus 5.5

Compare Claude Opus 5 and Claude Opus 5.5 side-by-side.

Compare Claude Opus 5 vs Claude Opus 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

Anthropic

Claude Opus 5 vs Claude Opus 5.5 on Vision Evals

Claude Opus 5.5 scores higher on 5 of the six Vision Evals tasks.

The widest gap is Object Detection, where Claude Opus 5.5 leads 74.4% to 54.4%.

Overall, Claude Opus 5 averages 78.3% (#16 of 57) against 85.5% (#3 of 57) for Claude Opus 5.5.

Claude Opus 5.5 is cheaper ($0.014 vs $0.017 per sample), while Claude Opus 5 is faster (7.4s vs 12.8s per sample).

Claude Opus 5Claude Opus 5.5

Claude Opus 5 vs Claude Opus 5.5 Comparison Table

Evals updated September 22, 2026Pricing updated September 22, 2026

PropertyClaude Opus 5Claude Opus 5.5
OrganizationAnthropicAnthropic
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJul 2026Sep 2026
Context Window1.0M1.0M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$5.00
Output $/1M$25.00
Vision Tasks
CaptioningDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Multi-Label Classification
Object DetectionDemo
OCRDemo
Vision Language
Visual Question AnsweringDemo
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%
85.5%
Avg cost / sample$0.017$0.014
Avg speed / sample7.38s12.76s
By task
Object Detection (low)
54.4%
$0.027
74.4%
±0.5, Mean of 3 runs, range 73.9 to 74.8
$0.022
Object Detection (high)
76.8%
±1.2, Mean of 3 runs, range 75.4 to 77.8
$0.030
Counting (low)
70.3%
$0.0096
80.6%
±2.0, Mean of 3 runs, range 78.4 to 82.4
$0.0081
Counting (high)
82.0%
±2.0, Mean of 3 runs, range 79.7 to 83.8
$0.0098
Identification (low)
90.6%
$0.0072
93.8%
±0.0, Mean of 3 runs, range 93.8 to 93.8
$0.0058
Identification (high)
95.8%
±1.6, Mean of 3 runs, range 93.8 to 96.9
$0.0067
OCR (low)
93.2%
$0.020
87.8%
±0.6, Mean of 3 runs, range 87.0 to 88.2
$0.017
OCR (high)
87.2%
±0.6, Mean of 3 runs, range 86.5 to 87.8
$0.024
Data Extraction (low)
89.7%
$0.0080
93.5%
±0.5, Mean of 3 runs, range 92.8 to 93.8
$0.0066
Data Extraction (high)
93.5%
±0.5, Mean of 3 runs, range 92.8 to 93.8
$0.0075
Reasoning (low)
71.5%
$0.010
83.0%
±1.0, Mean of 3 runs, range 82.1 to 84.1
$0.0090
Reasoning (high)
74.2%
$0.018
85.9%
±2.6, Mean of 3 runs, range 82.8 to 88.1
$0.011

Claude Opus 5 vs Claude Opus 5.5: Overview

Claude Opus 5

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 Opus 5.5

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 5 of the six vision tasks and averages 85.5% (#3 of 57) against 78.3% (#16 of 57) 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 Opus 5.5 leads with 74.4% against 54.4%. 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 $0.014 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 12.8s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.