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Gemini 3.1 Pro vs Grok 4.5

Compare Gemini 3.1 Pro and Grok 4.5 side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, Classification, OCR, and Object Detection.

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GoogleGemini 3.1 Pro
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GrokGrok 4.5
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Models in this comparison

Gemini 3.1 Pro vs Grok 4.5 on Vision Evals

Gemini 3.1 Pro scores higher on all six Vision Evals tasks.

The widest gap is Object Detection, where Gemini 3.1 Pro leads 67.4% to 19.0%.

Overall, Gemini 3.1 Pro averages 83.3% (#7 of 59) against 65.8% (#40 of 59) for Grok 4.5.

Grok 4.5 is cheaper ($0.0084 vs $0.0093 per sample), while Gemini 3.1 Pro is faster (7.8s vs 20.8s per sample).

Gemini 3.1 ProGrok 4.5

Gemini 3.1 Pro vs Grok 4.5 Comparison Table

Evals updated September 27, 2026Pricing updated September 27, 2026

PropertyGemini 3.1 ProGrok 4.5
OrganizationGoogleSpaceXAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateFeb 2026Jul 2026
Context Window1.0M500K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$2.00$2.00
Output $/1M$12.00$6.00
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
83.3%
65.8%
Avg cost / sample$0.0093$0.0084
Avg speed / sample7.81s20.75s
By task
Object Detection (low)
67.4%
$0.010
19.0%
±0.8, Mean of 3 runs, range 18.0 to 19.6
$0.011
Object Detection (high)–
17.8%
±0.3, Mean of 3 runs, range 17.5 to 18.0
$0.020
Counting (low)
71.6%
$0.0071
59.5%
±3.4, Mean of 3 runs, range 55.4 to 62.2
$0.0065
Counting (high)–
57.7%
±3.4, Mean of 3 runs, range 54.0 to 60.8
$0.012
Identification (low)
100.0%
$0.0070
83.3%
±1.6, Mean of 3 runs, range 81.3 to 84.4
$0.0046
Identification (high)–
85.4%
±3.1, Mean of 3 runs, range 81.3 to 87.5
$0.0067
OCR (low)
92.6%
$0.0066
92.1%
±0.3, Mean of 3 runs, range 91.9 to 92.5
$0.0068
OCR (high)–
92.3%
±0.5, Mean of 3 runs, range 91.9 to 92.9
$0.012
Data Extraction (low)
95.9%
$0.0063
83.5%
±1.6, Mean of 3 runs, range 81.4 to 84.5
$0.0044
Data Extraction (high)–
81.8%
±1.6, Mean of 3 runs, range 80.4 to 83.5
$0.0061
Reasoning (low)
72.2%
$0.012
57.6%
±1.7, Mean of 3 runs, range 55.6 to 58.9
$0.0082
Reasoning (high)
74.8%
$0.021
59.8%
±2.6, Mean of 3 runs, range 57.0 to 62.3
$0.019

Gemini 3.1 Pro vs Grok 4.5: Overview

Gemini 3.1 Pro

Gemini 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.

The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.

Grok 4.5

Grok 4.5 is a proprietary reasoning model from SpaceXAI (xAI) that accepts interleaved text and image input and returns text, with a 500,000 token context window. xAI positions it as a model for coding, agentic software work, and knowledge tasks, and states it was trained in the company's Memphis data centers on datasets spanning science, engineering, and mathematics. Its reinforcement learning stage covers hundreds of thousands of multi step software engineering tasks scored by automated checks and model based grading, and training is reported to have run on tens of thousands of NVIDIA GB300 GPUs using an asynchronous scheme in which multi hour agentic rollouts continue while learning proceeds in parallel, targeting long horizon autonomous operation rather than single turn inference.

For vision, the model consumes JPEG and PNG images in any order relative to text prompts, covering visual question answering, description of chart and document imagery, and reading text rendered inside a scene. Reasoning effort is configurable, and the model supports function calling and structured outputs, so image inputs can be interleaved with tool calls inside agent loops. xAI has not published a technical report, architecture details, or parameter count, and reported mixture of experts sizing figures come from secondary coverage rather than official documentation.

Frequently Asked Questions

On Roboflow's Vision Evals, Gemini 3.1 Pro performed better. It scores higher on all six vision tasks and averages 83.3% (#7 of 59) against 65.8% (#40 of 59) for Grok 4.5. 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, Gemini 3.1 Pro leads with 67.4% against 19.0%. This is the widest gap between the two models across the benchmark's tasks.

Grok 4.5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0084 per sample against $0.0093. Gemini 3.1 Pro is priced at $2.00 per 1M input tokens and $12.00 per 1M output; Grok 4.5 is priced at $2.00 per 1M input tokens and $6.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Gemini 3.1 Pro is faster. Across Roboflow's Vision Evals it averaged 7.8s per inference against 20.8s. 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 open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.