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Gemini 2.5 Pro vs GPT-5.6 Terra

Compare Gemini 2.5 Pro and GPT-5.6 Terra 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 Terra
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Models in this comparison

Gemini 2.5 Pro vs GPT-5.6 Terra on Vision Evals

Gemini 2.5 Pro scores higher on 3 of the six Vision Evals tasks.

The widest gap is Object Detection, where GPT-5.6 Terra leads 60.7% to 33.7%.

Overall, Gemini 2.5 Pro averages 66.0% (#22 of 31) against 72.4% (#13 of 31) for GPT-5.6 Terra.

Gemini 2.5 Pro is both cheaper ($0.0050 vs $0.0089 per sample) and faster (6.1s vs 7.2s per sample).

Gemini 2.5 ProGPT-5.6 Terra

Gemini 2.5 Pro vs GPT-5.6 Terra Comparison Table

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

PropertyGemini 2.5 ProGPT-5.6 Terra
OrganizationGoogleOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJun 2025Jul 2026
Context Window1.0M1.1M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$1.25$2.00
Output $/1M$10.00$12.00
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%
72.4%
Avg cost / sample$0.0050$0.0089
Avg speed / sample6.11s7.15s
By task
Object Detection
33.7%
$0.010
60.7%
$0.014
Counting
52.7%
$0.0012
67.6%
$0.0060
Identification
93.8%
$0.0012
78.1%
$0.0039
OCR
88.8%
$0.0047
88.8%
$0.013
Data Extraction
84.5%
$0.0013
79.4%
$0.0037
Reasoning (low)
42.4%
$0.0013
59.6%
$0.0050
Reasoning (high)
62.3%
$0.011
64.2%
$0.0066

Gemini 2.5 Pro vs GPT-5.6 Terra: 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 Terra

GPT-5.6 Terra is the mid-tier reasoning model in OpenAI's GPT-5.6 family, which also includes the flagship Sol and the lightweight Luna. Introduced in a limited preview on June 26, 2026, and made broadly available on July 9, 2026, Terra accepts text and image input and produces text output, supporting vision, function calling, tool use, and agentic workflows. It is designed as a balanced option for everyday professional and production workloads — including coding assistance, document analysis, customer support, and multi-step agent tasks — where both output quality and cost efficiency matter. OpenAI positions Terra as delivering performance competitive with GPT-5.5 at approximately half the price, with a context window of around 1,050,000 tokens. On Terminal-Bench 2.1, Terra scores 84.3%, matching Claude Fable 5 on that benchmark. Under OpenAI's Preparedness Framework, Terra is rated High for cybersecurity and biological capabilities, meaning it demonstrates meaningful capability in those domains without reaching the Critical threshold.

GPT-5.6 introduces a new naming convention in which the generation number (5.6) is paired with a durable capability tier name (Sol, Terra, or Luna), allowing each tier to advance on its own schedule. Terra carries the API identifier gpt-5.6-terra and supports the same reasoning effort controls available across the family, including adjustable reasoning depth. The model includes prompt caching with explicit cache breakpoints and a 30-minute minimum cache life, with cache writes billed at 1.25x the uncached input rate and cache reads receiving a 90% discount. GPT-5.6 Terra is a proprietary, closed-weights model served through the OpenAI API, Codex, and ChatGPT.

Frequently Asked Questions

On Roboflow's Vision Evals, GPT-5.6 Terra performed slightly better overall. The two split the six vision tasks 3 to 3, but GPT-5.6 Terra averages 72.4% (#13 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 Terra leads with 60.7% 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 Terra is priced at $2.00 per 1M input tokens and $12.00 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 7.2s. 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.