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GPT-5.5 vs GPT-5.6 Sol

Compare GPT-5.5 and GPT-5.6 Sol side-by-side. See how these vision models stack up in Object Detection, Image Captioning, Classification, Open Prompt, and OCR.

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Models in this comparison

OpenAI

GPT-5.5 vs GPT-5.6 Sol on Vision Evals

GPT-5.5 scores higher on 3 of the six Vision Evals tasks.

The widest gap is Object Detection, where GPT-5.6 Sol leads 68.4% to 43.6%.

Overall, GPT-5.5 averages 74.8% (#21 of 60) against 79.0% (#16 of 60) for GPT-5.6 Sol.

GPT-5.6 Sol is cheaper ($0.0088 vs $0.022 per sample), while GPT-5.5 is faster (9.0s vs 10.3s per sample).

GPT-5.5GPT-5.6 Sol

GPT-5.5 vs GPT-5.6 Sol Comparison Table

Evals updated October 7, 2026Pricing updated October 7, 2026

PropertyGPT-5.5GPT-5.6 Sol
OrganizationOpenAIOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateApr 2026Jul 2026
Context Window1.0M1.5M
ParametersUnknownUnknown
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$5.00$2.00
Output $/1M$30.00$10.00
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 6 vision tasks, pooled at low effort
Overall
74.8%
79.0%
Avg cost / sample$0.022$0.0088
Avg speed / sample9.03s10.32s
By task
Object Detection (low)
43.6%
±2.2, Mean of 3 runs, range 41.7 to 46.1
$0.034
68.4%
±0.7, Mean of 3 runs, range 67.9 to 69.3
$0.015
Object Detection (high)
44.2%
±0.6, Mean of 3 runs, range 43.5 to 44.8
$0.130
68.4%
±0.8, Mean of 3 runs, range 67.7 to 69.3
$0.035
Counting (low)
68.0%
±3.4, Mean of 3 runs, range 64.9 to 71.6
$0.015
74.3%
±1.4, Mean of 3 runs, range 73.0 to 75.7
$0.0049
Counting (high)
68.0%
±1.4, Mean of 3 runs, range 66.2 to 68.9
$0.049
76.1%
±2.0, Mean of 3 runs, range 74.3 to 78.4
$0.0078
Identification (low)
89.6%
±1.6, Mean of 3 runs, range 87.5 to 90.6
$0.0087
89.6%
±4.7, Mean of 3 runs, range 84.4 to 93.8
$0.0028
Identification (high)
88.5%
±1.6, Mean of 3 runs, range 87.5 to 90.6
$0.018
92.7%
±1.6, Mean of 3 runs, range 90.6 to 93.8
$0.0030
OCR (low)
91.2%
±0.3, Mean of 3 runs, range 90.9 to 91.6
$0.024
90.7%
±0.1, Mean of 3 runs, range 90.6 to 90.7
$0.011
OCR (high)
91.7%
±0.6, Mean of 3 runs, range 91.1 to 92.3
$0.072
90.2%
±0.2, Mean of 3 runs, range 90.0 to 90.4
$0.025
Data Extraction (low)
85.9%
±1.5, Mean of 3 runs, range 84.5 to 87.6
$0.011
84.9%
±1.0, Mean of 3 runs, range 83.5 to 85.6
$0.0033
Data Extraction (high)
86.9%
±0.5, Mean of 3 runs, range 86.6 to 87.6
$0.019
86.9%
±0.5, Mean of 3 runs, range 86.6 to 87.6
$0.0041
Reasoning (low)
70.6%
±1.0, Mean of 3 runs, range 69.5 to 71.5
$0.015
66.0%
±2.6, Mean of 3 runs, range 63.6 to 68.9
$0.0043
Reasoning (high)
72.2%
±3.6, Mean of 3 runs, range 68.9 to 76.2
$0.044
71.7%
±1.3, Mean of 3 runs, range 70.2 to 72.8
$0.0061

GPT-5.5 vs GPT-5.6 Sol: Overview

GPT-5.5

GPT-5.5 is a multimodal large language model released by OpenAI on April 23, 2026, engineered for autonomous, multi-step knowledge work and agentic workflows. It accepts text, images, and code as input, featuring enhanced spatial reasoning and visual grounding to support its computer use capabilities for operating software and navigating UI elements. Built to execute complex workflows end-to-end, the model interprets loosely defined tasks, selects appropriate tools, and performs self-verification with minimal user intervention. It is available in a standard version, a Thinking mode for extended reasoning budgets, and a Pro variant that uses parallel test-time compute for maximum precision on complex tasks.

Co-optimized with NVIDIA for GB200 NVL72 infrastructure, GPT-5.5 delivers per-token latency comparable to its predecessor GPT-5.4 while maintaining a 1-million-token context window. Despite increased capability, the model achieves greater token efficiency in coding and data analysis workflows, often completing tasks with fewer total tokens than previous versions. OpenAI reports a 60% reduction in hallucination rate compared to GPT-5.4, improving reliability for accuracy-sensitive applications. API access is available via the Responses and Chat Completions endpoints.

GPT-5.6 Sol

GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 family, which also includes Terra (a balanced everyday-work tier) and Luna (a fast, cost-efficient tier). Sol is designed for demanding reasoning, long-horizon agentic workflows, software engineering, computer use, scientific research, and cybersecurity tasks. It introduces two new capability modes: a "max" reasoning effort setting that allocates additional compute time for difficult problems, and an "ultra" mode that coordinates multiple subagents in parallel to accelerate complex, multi-step work. The model supports native multimodal input, allowing it to process screenshots, diagrams, charts, documents, and photographs alongside text. A reported context window of approximately 1.5 million tokens enables processing of large codebases, lengthy research documents, and extended agentic sessions.

GPT-5.6 Sol was announced on June 26, 2026, initially in a limited preview for trusted partners, and reached general availability on July 9, 2026. On the Agents' Last Exam benchmark, which evaluates long-running professional workflows across 55 fields, Sol scores 53.6. On Terminal-Bench 2.1, which tests command-line agentic coding workflows, Sol Ultra achieves 91.9%. The model also demonstrates gains in life sciences evaluations, including long-horizon genomics and quantitative biology analyses. OpenAI paired the release with its most extensive safety evaluation to date, combining human red teaming with large-scale automated testing, and classified Sol as High capability in both cybersecurity and biological risk under its Preparedness Framework, though it does not cross the Critical threshold in either category.