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Gemini 2.5 Pro vs GPT-5.6 Sol

Compare Gemini 2.5 Pro and GPT-5.6 Sol side-by-side. See how these vision models stack up in Object Detection, Open Prompt, Classification, OCR, and Image Captioning.

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GoogleGemini 2.5 Pro
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OpenAIGPT-5.6 Sol
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Models in this comparison

Gemini 2.5 Pro vs GPT-5.6 Sol on Vision Evals

GPT-5.6 Sol scores higher on 4 of the six Vision Evals tasks.

The widest gap is Object Detection, where GPT-5.6 Sol leads 68.2% to 33.7%.

Overall, Gemini 2.5 Pro averages 66.0% (#22 of 31) against 76.9% (#10 of 31) for GPT-5.6 Sol.

Gemini 2.5 Pro is both cheaper ($0.0050 vs $0.0089 per sample) and faster (6.1s vs 11.7s per sample).

Gemini 2.5 ProGPT-5.6 Sol

Gemini 2.5 Pro vs GPT-5.6 Sol Comparison Table

Evals updated August 20, 2026Pricing updated August 24, 2026

PropertyGemini 2.5 ProGPT-5.6 Sol
OrganizationGoogleOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJun 2025Jul 2026
Context Window1.0M1.5M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$1.25$2.00
Output $/1M$10.00$10.00
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemoDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
66.0%
76.9%
Avg cost / sample$0.0050$0.0089
Avg speed / sample6.11s11.72s
By task
Object Detection
33.7%
$0.010
68.2%
$0.016
Counting
52.7%
$0.0012
73.0%
$0.0048
Identification
93.8%
$0.0012
81.3%
$0.0027
OCR
88.8%
$0.0047
90.7%
$0.011
Data Extraction
84.5%
$0.0013
82.5%
$0.0033
Reasoning (low)
42.4%
$0.0013
65.6%
$0.0042
Reasoning (high)
62.3%
$0.011
72.2%
$0.0057

Gemini 2.5 Pro vs GPT-5.6 Sol: Overview

Gemini 2.5 Pro

Gemini 2.5 Pro, released on June 17, 2025, is Google DeepMind’s most capable model in the Gemini 2.5 family, optimized for deep reasoning, coding, and complex multimodal tasks. It accepts text, images, audio, video, and PDFs as input and outputs text. The model supports 1 million input tokens with an output capacity of up to 65K tokens, enabling large-scale comprehension of datasets, codebases, and technical documents. Its training knowledge extends to January 2025.

Pro outperforms earlier Gemini 2.0 models across benchmarks, including agentic coding tasks where it achieved ~63.8% on SWE-Bench Verified. It supports structured outputs, function calling, code execution, search grounding, and URL context, making it well-suited for enterprise, STEM, and developer workflows. However, it does not currently support image or audio generation in its stable release, and its higher computational cost and latency make it less efficient than Flash or Flash-Lite. It is available via the Gemini API, Google AI Studio, and Vertex AI.

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.

Frequently Asked Questions

On Roboflow's Vision Evals, GPT-5.6 Sol performed better. It scores higher on 4 of the six vision tasks and averages 76.9% (#10 of 31) against 66.0% (#22 of 31) for Gemini 2.5 Pro. 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, GPT-5.6 Sol leads with 68.2% against 33.7%. This is the widest gap between the two models across the benchmark's tasks.

Gemini 2.5 Pro is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0050 per sample against $0.0089. Gemini 2.5 Pro is priced at $1.25 per 1M input tokens and $10.00 per 1M output; GPT-5.6 Sol is priced at $2.00 per 1M input tokens and $10.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Gemini 2.5 Pro is faster. Across Roboflow's Vision Evals it averaged 6.1s per inference against 11.7s. 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 object detection and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.