Gemini 2.5 Flash-Lite vs YOLO World

Compare Gemini 2.5 Flash-Lite and YOLO World side-by-side. See how these vision models stack up in Object Detection.

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GoogleGemini 2.5 Flash-Lite
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TencentYOLO World
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Models in this comparison

Tencent

Gemini 2.5 Flash-Lite vs YOLO World: 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.

YOLO World

YOLO-World v2 Small (YOLO-World-S-v2) is the smallest variant of Tencent AI Lab’s YOLO-World v2 family, released around February 2024 under GPL-v3. With ~13 million parameters, it adopts a prompt-then-detect paradigm using offline vocabularies and is pretrained on large-scale datasets such as Objects365 and GoldG. The model processes image inputs at 640×640 or 1280×1280 resolutions and supports zero-shot open-vocabulary object detection, enabling recognition of novel categories from text prompts without retraining.

Evaluations show competitive results across benchmarks like LVIS and COCO, while maintaining real-time efficiency. On an NVIDIA V100, the small variant reaches ~74 FPS at standard resolutions. Together with larger YOLO-World v2 models, it provides a scalable framework for efficient, open-vocabulary detection across diverse deployment settings.

Gemini 2.5 Flash-Lite vs YOLO World Comparison Table

PropertyGemini 2.5 Flash-LiteYOLO World
OrganizationGoogleTencent AI Lab
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateJul 2025Feb 2024
Context Window1.0M13.0M
Parameters
LicenseProprietaryGPL v3
Pricing per 1M tokens
Input $/1M$0.100
Output $/1M$0.400
Vision Tasks
Object DetectionDemoDemo
CaptioningDemo
ClassificationDemo
OCRDemo
Open Vocabulary Object Detection
Phrase Grounding
Vision Language
Visual Question AnsweringDemo
Model Features
Multimodal Vision
Foundation Vision
LLMs with Vision Capabilities
Real-Time Vision
Zero-shot Detection
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Overall Score
53.73%
Avg Response Time7.19s
Median input tokensincl. image tokens294
Median output tokens6
Est. cost / taskon this benchmark$0.0000
Defect Detection
66.7%(10/15)
Document Understanding
66.7%(6/9)
Object Counting
10%(1/10)
Object Understanding
71.4%(10/14)
Spatial Understanding
47.4%(9/19)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology