Roboflow

Claude Haiku 5.5 vs Claude Opus 5

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

Compare Claude Haiku 5.5 vs Claude Opus 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 Haiku 5.5 vs Claude Opus 5 on Vision Evals

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

The widest gap is Object Detection, where Claude Haiku 5.5 leads 65.8% to 54.4%.

Overall, Claude Haiku 5.5 averages 77.2% (#20 of 61) against 78.3% (#18 of 61) for Claude Opus 5.

Claude Haiku 5.5 is cheaper ($0.0005 vs $0.017 per sample), while Claude Opus 5 is faster (7.4s vs 13.2s per sample).

Claude Haiku 5.5Claude Opus 5

Claude Haiku 5.5 vs Claude Opus 5 Comparison Table

Evals updated October 8, 2026Pricing updated October 8, 2026

PropertyClaude Haiku 5.5Claude Opus 5
OrganizationAnthropicAnthropic
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateOct 2026Jul 2026
Context Window1.0M1.0M
ParametersundisclosedUnknown
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.100$5.00
Output $/1M$0.500$25.00
Vision Tasks
CaptioningSupportedDemo
Chart Question AnsweringSupportedSupported
ClassificationSupportedDemo
Document Question AnsweringSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionSupportedDemo
OCRSupportedDemo
Vision LanguageSupportedSupported
Visual Question AnsweringSupportedDemo
Image TaggingSupportedNot listed
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
77.2%
78.3%
Avg cost / sample$0.0005$0.017
Avg speed / sample13.23s7.38s
By task
Object Detection (low)
65.8%
±0.6, Mean of 3 runs, range 65.1 to 66.2
$0.0006
54.4%
$0.027
Object Detection (high)
68.2%
±1.0, Mean of 3 runs, range 67.2 to 69.2
$0.0010
–
Counting (low)
68.9%
±4.7, Mean of 3 runs, range 64.9 to 74.3
$0.0003
70.3%
$0.0096
Counting (high)
73.0%
±1.3, Mean of 3 runs, range 71.6 to 74.3
$0.0004
–
Identification (low)
83.3%
±3.1, Mean of 3 runs, range 81.3 to 87.5
$0.0002
90.6%
$0.0072
Identification (high)
86.5%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.0003
–
OCR (low)
90.1%
±1.1, Mean of 3 runs, range 88.8 to 91.0
$0.0006
93.2%
$0.020
OCR (high)
88.0%
±1.3, Mean of 3 runs, range 87.0 to 89.6
$0.0009
–
Data Extraction (low)
85.9%
±1.5, Mean of 3 runs, range 84.5 to 87.6
$0.0002
89.7%
$0.0080
Data Extraction (high)
87.3%
±0.5, Mean of 3 runs, range 86.6 to 87.6
$0.0002
–
Reasoning (low)
68.9%
±2.0, Mean of 3 runs, range 66.9 to 70.9
$0.0004
71.5%
$0.010
Reasoning (high)
74.8%
±2.6, Mean of 3 runs, range 72.2 to 77.5
$0.0006
74.2%
$0.018

Claude Haiku 5.5 vs Claude Opus 5: Overview

Claude Haiku 5.5

Claude Haiku 5.5 is a proprietary multimodal language model from Anthropic and the smallest member of the Claude 5.5 family, released on October 7, 2026 after Claude Opus 5.5 and Claude Sonnet 5.5. It accepts text and image input and returns text, with a 1M token context window and up to 128K output tokens per request. It is the first Haiku-class model with an adjustable effort parameter: adaptive thinking is on by default and the model decides how much to reason, steered by effort levels from low to max with medium as the default. Its training data cutoff is June 2026. Pricing starts at $0.10 per million input tokens and $0.50 per million output tokens for prompts up to 100K tokens, which Anthropic reports is about 90% lower than Claude Haiku 4.5 for requests in that range.

Anthropic positions Haiku 5.5 for high-volume, latency-sensitive work such as classification, extraction, routing, summarization, and subagent tasks, and describes it as its fastest model to date at standard speed. On visual and agentic evaluations reported at launch, it scores 46.4% on Chartography, a chart reading benchmark, compared with 6.4% for Haiku 4.5 and 61.6% for Sonnet 5.5, and 72.4% on the offline subset of OSWorld 2.1, a screenshot driven computer use benchmark, compared with 15.7% for Haiku 4.5. It uses the same tokenizer as Claude Opus 4.7 and later models, so the same text counts as roughly 30% more tokens than on Haiku 4.5.

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 a lower cost. 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.

Frequently Asked Questions

On Roboflow's Vision Evals, Claude Opus 5 performed better. It scores higher on 5 of the six vision tasks and averages 78.3% (#18 of 61) against 77.2% (#20 of 61) for Claude Haiku 5.5. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

Yes. On the Vision Evals Object Detection benchmark at low effort, Claude Haiku 5.5 leads with 65.8% against 54.4%. This is the widest gap between the two models across the benchmark's tasks.

Claude Haiku 5.5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0005 per sample against $0.017. Claude Haiku 5.5 is priced at $0.10 per 1M input tokens and $0.50 per 1M output; Claude Opus 5 is priced at $5.00 per 1M input tokens and $25.00 per 1M output. 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 13.2s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.