Gemini 2.5 Flash-Lite vs Qwen3.5 397B A17B

Compare Gemini 2.5 Flash-Lite and Qwen3.5 397B A17B side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.

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GoogleGemini 2.5 Flash-Lite
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QwenQwen3.5 397B A17B
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Gemini 2.5 Flash-Lite vs Qwen3.5 397B A17B: 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.

Qwen3.5 397B A17B

Qwen3.5-397B-A17B is a 397B-parameter (17B active) open-weight multimodal model developed by Alibaba’s Qwen team, released on 2026-02-16 under Apache-2.0. It supports text and image inputs with text outputs, combining a sparse Mixture-of-Experts architecture with Gated Delta Networks for efficient scaling. The model provides native vision-language reasoning and a large ~262K token context window, extendable to ~1M tokens.

As the first open-weight release in the Qwen3.5 family, it positions itself as a high-capacity, long-context alternative in the large vision-language space, balancing scale and efficiency via sparse activation. It is designed for advanced reasoning, coding, agent workflows, and multimodal understanding tasks.

Gemini 2.5 Flash-Lite vs Qwen3.5 397B A17B Comparison Table

PropertyGemini 2.5 Flash-LiteQwen3.5 397B A17B
OrganizationGoogleQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateJul 2025Feb 2026
Context Window1.0M262K
Parameters397B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$0.100$0.385
Output $/1M$0.400$2.45
Vision Tasks
CaptioningDemoDemo
Object DetectionDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
ClassificationDemo
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Overall Score
53.73%
58.21%
Avg Response Time7.19s56.61s
Median input tokensincl. image tokens2941.1K
Median output tokens654
Est. cost / taskon this benchmark$0.0000$0.0006
Defect Detection
66.7%(10/15)
66.7%(10/15)
Document Understanding
66.7%(6/9)
77.8%(7/9)
Object Counting
10%(1/10)
20%(2/10)
Object Understanding
71.4%(10/14)
64.3%(9/14)
Spatial Understanding
47.4%(9/19)
57.9%(11/19)

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