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Gemini 2.5 Flash vs Llama 3.2 Vision 11b

Compare Gemini 2.5 Flash and Llama 3.2 Vision 11b side-by-side. See how these vision models stack up in Open Prompt, OCR, Classification, and Image Captioning.

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GoogleGemini 2.5 Flash
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MetaLlama 3.2 Vision 11b
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Gemini 2.5 Flash vs Llama 3.2 Vision 11b Comparison Table

Evals updated July 10, 2026Pricing updated July 21, 2026

PropertyGemini 2.5 FlashLlama 3.2 Vision 11b
OrganizationGoogleMeta
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateJul 2025Sep 2024
Context Window1.0M128K
Parameters11B
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.300
Output $/1M$2.50
Vision Tasks
CaptioningDemoDemo
ClassificationDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Object DetectionDemo
Model Features
Multimodal Vision
Foundation Vision
LLMs with Vision Capabilities

Gemini 2.5 Flash vs Llama 3.2 Vision 11b: 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.

Llama 3.2 Vision 11b

Llama 3.2 Vision 11B, released by Meta on September 25, 2024, is the first mid-sized model in the Llama family with vision capabilities, supporting both text and image inputs with text-only outputs. It contains around 11 billion parameters (~10.6B) and features a 128,000-token context window, making it suitable for multimodal reasoning over long documents and image-text tasks. The model was trained on ~6 billion image–text pairs and has a knowledge cutoff of December 2023.

The model is available in a base and an instruction-tuned (“Vision-Instruct”) version, optimized for tasks like captioning, visual question answering, and image reasoning. It leverages Group-Query Attention (GQA) for improved inference efficiency and scalability. While text tasks officially support multiple languages (English, German, French, Italian, Portuguese, Hindi, Spanish, Thai), multimodal (image+text) tasks are supported primarily in English. Llama 3.2 Vision 11B is accessible through Hugging Face, Amazon Bedrock, Azure AI Foundry, NVIDIA NIM, and OCI, making it a widely deployable open-weight multimodal foundation model.