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Gemini 2.5 Flash-Lite vs Qwen-VL

Compare Gemini 2.5 Flash-Lite and Qwen-VL side-by-side.

Compare Gemini 2.5 Flash-Lite vs Qwen-VL live

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Gemini 2.5 Flash-Lite vs Qwen-VL Comparison Table

Evals updated July 24, 2026Pricing updated July 26, 2026

PropertyGemini 2.5 Flash-LiteQwen-VL
OrganizationGoogleQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateJul 2025Aug 2023
Context Window1.0M
Parameters
LicenseProprietaryCustom
Pricing per 1M tokens
Input $/1M$0.100
Output $/1M$0.400
Vision Tasks
CaptioningDemo
Vision Language
Visual Question AnsweringDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemo
OCRDemo
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision

Gemini 2.5 Flash-Lite vs Qwen-VL: 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.

Qwen-VL

Qwen-VL is a large vision-language model released in August 2023 by the Qwen team at Alibaba Cloud. Built on the 7-billion-parameter Qwen language model with an added visual receptor based on Openclip ViT-bigG, the model accepts images, text, and bounding box coordinates as inputs, and can produce both text and bounding boxes as outputs. Qwen-VL processes images at 448×448 resolution, higher than the 224×224 input used by many contemporaneous vision-language models, which supports finer-grained visual recognition and text-heavy tasks such as OCR. This design supports a range of multimodal tasks in a single model, including image captioning, visual question answering, visual grounding, text recognition, and image-conditioned dialogue, with native support for English, Chinese, and multilingual conversation.

At release, Qwen-VL achieved competitive results against contemporaneous vision-language models across zero-shot captioning, general VQA, text-oriented VQA, and referring expression comprehension benchmarks. A chat-tuned variant, Qwen-VL-Chat, is optimized for interactive use with instruction-following and multi-turn conversation. The model is distributed under the Tongyi Qianwen License, a custom license from Alibaba Cloud with specific terms that should be reviewed prior to commercial use. Qwen-VL is the first generation of Alibaba's open multimodal series and precedes the later Qwen2-VL and Qwen2.5-VL releases.