Roboflow

Claude Sonnet 5.5 vs GPT-5.4 Mini

Compare Claude Sonnet 5.5 and GPT-5.4 Mini side-by-side. See how these vision models stack up in Image Captioning, OCR, Classification, Object Detection, and Open Prompt.

Compare Claude Sonnet 5.5 vs GPT-5.4 Mini 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.

Open Object Detection in the full playground
AnthropicClaude Sonnet 5.5
Run to compare this model.
OpenAIGPT-5.4 Mini
Run to compare this model.

Models in this comparison

Claude Sonnet 5.5 vs GPT-5.4 Mini on Vision Evals

Claude Sonnet 5.5 scores higher on all five Vision Evals tasks.

The widest gap is Object Detection, where Claude Sonnet 5.5 leads 74.3% to 15.8%.

Overall, Claude Sonnet 5.5 averages 77.6% (#8 of 61) against 53.2% (#49 of 61) for GPT-5.4 Mini.

GPT-5.4 Mini is both cheaper ($0.0034 vs $0.0073 per sample) and faster (5.5s vs 8.3s per sample).

Claude Sonnet 5.5GPT-5.4 Mini

Claude Sonnet 5.5 vs GPT-5.4 Mini Comparison Table

Evals updated October 8, 2026Pricing updated October 9, 2026

PropertyClaude Sonnet 5.5GPT-5.4 Mini
OrganizationAnthropicOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026Mar 2026
Context Window1.0M400K
ParametersUnknownUnknown
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$2.00$0.750
Output $/1M$10.00$4.50
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationDemoDemo
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoDemo
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
77.6%
53.2%
Avg cost / sample$0.0073$0.0034
Avg speed / sample8.33s5.51s
By task
Object Detection (low)
74.3%
±0.9, Mean of 3 runs, range 73.5 to 75.3
$0.0098
15.8%
±0.4, Mean of 3 runs, range 15.3 to 16.1
$0.0044
Object Detection (high)
76.8%
±0.4, Mean of 3 runs, range 76.5 to 77.3
$0.014
16.6%
±0.8, Mean of 3 runs, range 15.8 to 17.4
$0.030
Counting (low)
79.3%
±0.7, Mean of 3 runs, range 78.4 to 79.7
$0.0042
58.6%
±2.0, Mean of 3 runs, range 56.8 to 60.8
$0.0019
Counting (high)
82.9%
±1.4, Mean of 3 runs, range 81.1 to 83.8
$0.0053
64.9%
±2.0, Mean of 3 runs, range 63.5 to 67.6
$0.0073
Identification (low)
91.7%
±3.1, Mean of 3 runs, range 87.5 to 93.8
$0.0029
83.3%
±1.6, Mean of 3 runs, range 81.3 to 84.4
$0.0013
Identification (high)
90.6%
±0.0, Mean of 3 runs, range 90.6 to 90.6
$0.0033
82.3%
±3.1, Mean of 3 runs, range 78.1 to 84.4
$0.0055
OCR (low)
66.3%
$0.0075
51.1%
$0.0035
by category
Single value
48.7%
Transcription
76.3%
Structured JSON
83.8%
Text localization
60.6%
Single value
41.3%
Transcription
77.3%
Structured JSON
73.6%
Text localization
4.1%
OCR (high)–
55.8%
$0.027
by category
Single value
47.0%
Transcription
78.5%
Structured JSON
79.0%
Text localization
6.1%
Reasoning (low)
76.4%
±0.7, Mean of 3 runs, range 75.5 to 76.8
$0.0049
57.0%
±3.3, Mean of 3 runs, range 54.3 to 60.9
$0.0022
Reasoning (high)
83.9%
±1.7, Mean of 3 runs, range 82.1 to 85.4
$0.0061
64.0%
±1.3, Mean of 3 runs, range 62.9 to 65.6
$0.0096

Claude Sonnet 5.5 vs GPT-5.4 Mini: Overview

Claude Sonnet 5.5

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.

GPT-5.4 Mini

GPT-5.4 mini is a fast, cost-efficient model developed by OpenAI and released on March 17, 2026, optimized for high-throughput workloads and subagent orchestration. It supports text and image inputs within a 400,000-token context window, making it ideal for processing extensive visual datasets and large codebases in a single request. Designed for low-latency production environments, the model integrates with key API features including function calling, web search, and tool-based computer use, allowing it to assist in automated workflows that require navigating digital interfaces.

Compared to the previous GPT-5 mini, this version runs more than twice as fast while approaching the performance levels of the flagship GPT-5.4 on reasoning and coding benchmarks. While the larger GPT-5.4 introduces native, state-of-the-art computer-use capabilities, GPT-5.4 mini provides a scalable alternative for interpreting screenshots and reasoning over dense UI layouts. For vision tasks on Playground, it excels at extracting structured information from visual documents and assisting in agentic tasks that involve real-time interpretation of software interfaces alongside text.

Frequently Asked Questions

On Roboflow's Vision Evals, Claude Sonnet 5.5 performed better. It scores higher on all five vision tasks and averages 77.6% (#8 of 61) against 53.2% (#49 of 61) for GPT-5.4 Mini. 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 Sonnet 5.5 leads with 74.3% against 15.8%. This is the widest gap between the two models across the benchmark's tasks.

GPT-5.4 Mini is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0034 per sample against $0.0073. Claude Sonnet 5.5 is priced at $2.00 per 1M input tokens and $10.00 per 1M output; GPT-5.4 Mini is priced at $0.75 per 1M input tokens and $4.50 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

GPT-5.4 Mini is faster. Across Roboflow's Vision Evals it averaged 5.5s per inference against 8.3s. 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 OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.