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Gemini 2.5 Flash vs Grok 4.5

Compare Gemini 2.5 Flash and Grok 4.5 side-by-side. See how these vision models stack up in Open Prompt, OCR, Classification, Image Captioning, and Object Detection.

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Models in this comparison

Gemini 2.5 Flash vs Grok 4.5 Comparison Table

Evals updated September 29, 2026Pricing updated September 29, 2026

PropertyGemini 2.5 FlashGrok 4.5
OrganizationGoogleSpaceXAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJul 2025Jul 2026
Context Window1.0M500K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.300$2.00
Output $/1M$2.50$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
OverallNot evaluated
65.8%
Avg cost / sample–$0.0084
Avg speed / sample–20.75s
By task
Object Detection (low)–
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)–
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)–
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)–
92.1%
±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)–
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)–
57.6%
±1.7, Mean of 3 runs, range 55.6 to 58.9
$0.0082
Reasoning (high)–
59.8%
±2.6, Mean of 3 runs, range 57.0 to 62.3
$0.019

Gemini 2.5 Flash vs Grok 4.5: Overview

Gemini 2.5 Flash

Gemini 2.5 Flash, released on June 17, 2025, is Google DeepMind’s production-ready, efficiency-focused model in the Gemini 2.5 family. It is multimodal, accepting text, images, video, and audio as inputs, with text as the primary output format. The model supports 1 million input tokens and up to 65K output tokens, enabling it to process very large contexts such as books, long video transcripts, or extensive datasets. Its training knowledge extends to January 2025.

Designed as a price-performance leader, Gemini 2.5 Flash balances speed and reasoning power, making it suitable for everyday enterprise and developer use cases without the higher latency and cost of Pro models. It supports advanced workflows like function calling, code execution, search grounding, URL context ingestion, and structured outputs. While efficient and scalable, output length is still limited compared to its input capacity, and multimodal outputs (e.g. image or audio generation) remain restricted to specialized or preview variants.

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

Gemini 2.5 Flash has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.

Yes. The comparison demo on this page runs both models on the same image side by side for open prompts and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.