Roboflow

Gemini 2.5 Flash-Lite vs GPT-6.1 Sol

Compare Gemini 2.5 Flash-Lite and GPT-6.1 Sol side-by-side. See how these vision models stack up in Image Captioning, Object Detection, OCR, Open Prompt, and Classification.

Compare Gemini 2.5 Flash-Lite vs GPT-6.1 Sol live

Run the same image across every model that supports a task and compare their outputs side-by-side.

Detect and compare bounding boxes across models on the same image.

Open Object Detection in the full playground
GoogleGemini 2.5 Flash-Lite
Run to compare this model.
OpenAIGPT-6.1 Sol
Run to compare this model.

Models in this comparison

Gemini 2.5 Flash-Lite vs GPT-6.1 Sol Comparison Table

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

PropertyGemini 2.5 Flash-LiteGPT-6.1 Sol
OrganizationGoogleOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJul 2025Sep 2026
Context Window1.0M1.1M
Parametersundisclosed
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.100$2.00
Output $/1M$0.400$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
Promptable Concept SegmentationDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
OverallNot evaluated
85.5%
Avg cost / sample–$0.0061
Avg speed / sample–14.31s
By task
Object Detection (low)–
80.8%
±0.1, Mean of 3 runs, range 80.7 to 80.9
$0.010
Object Detection (high)–
81.6%
±0.4, Mean of 3 runs, range 81.1 to 82.0
$0.022
Counting (low)–
78.8%
±3.4, Mean of 3 runs, range 75.7 to 82.4
$0.0037
Counting (high)–
80.2%
±3.4, Mean of 3 runs, range 77.0 to 83.8
$0.0057
Identification (low)–
89.6%
±1.6, Mean of 3 runs, range 87.5 to 90.6
$0.0025
Identification (high)–
88.5%
±1.6, Mean of 3 runs, range 87.5 to 90.6
$0.0030
OCR (low)–
92.0%
±0.5, Mean of 3 runs, range 91.5 to 92.5
$0.0064
OCR (high)–
91.7%
±0.3, Mean of 3 runs, range 91.2 to 91.9
$0.017
Data Extraction (low)–
88.0%
±0.5, Mean of 3 runs, range 87.6 to 88.7
$0.0030
Data Extraction (high)–
90.0%
±1.0, Mean of 3 runs, range 88.7 to 90.7
$0.0037
Reasoning (low)–
83.7%
±1.3, Mean of 3 runs, range 82.1 to 84.8
$0.0033
Reasoning (high)–
88.7%
±2.0, Mean of 3 runs, range 87.4 to 91.4
$0.0042

Gemini 2.5 Flash-Lite vs GPT-6.1 Sol: Overview

Gemini 2.5 Flash-Lite

Gemini 2.5 Flash-Lite, released for general availability on July 22, 2025, is the most cost-efficient model in the Gemini 2.5 family, designed for high-volume and latency-sensitive tasks. It is multimodal, supporting text, images, video, audio, and PDFs as inputs, with text as its primary output. The model handles up to 1 million input tokens and generates outputs up to 64K tokens, making it suitable for large-scale document or media processing at low cost. It is built on a Sparse Mixture-of-Experts architecture with native multimodal support, though exact parameter counts are undisclosed.

Flash-Lite offers the lowest usage cost among Gemini 2.5 models. It introduces developer controls for “thinking mode,” allowing fine-tuning of reasoning depth vs. efficiency. It also integrates native tools such as code execution, search grounding, and URL context. While strong on translation, classification, coding, and general multimodal reasoning, it lacks support for image or audio generation in its stable release and is less capable than Gemini 2.5 Flash or Pro on complex reasoning-heavy workflows.

GPT-6.1 Sol

GPT-6.1 Sol is a reasoning model in OpenAI's GPT-6 series that accepts text and image input and returns text. It is an upgrade to GPT-6 Sol positioned to approach the intelligence of the larger GPT-6 Astra model on agentic coding, computer use, and professional knowledge work. The model exposes an adjustable reasoning effort control, ranging from low settings for simple turns to maximum settings for harder tasks, and can be driven with tool use enabled or disabled. It operates over a context window of roughly one million tokens and emits up to 128,000 output tokens in a single response, which supports long-running agent loops over large codebases and multi-document collections. Audio and video inputs are not supported.

On the visual side, the model is evaluated on GDP.pdf, a benchmark that asks professional questions about complex PDF documents containing tables, charts, diagrams, and fine-print details, and on OSWorld 2.0, which measures agents operating graphical computer applications. OpenAI reports that GPT-6.1 Sol performs on par with or better than GPT-6 Sol across its image input safety evaluations, and that the share of responses containing a factual error at low reasoning effort falls from 11.4 percent to 7.7 percent.

Frequently Asked Questions

Gemini 2.5 Flash-Lite 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 image captioning and object detection in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.