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Gemini 3 Pro vs Kimi K2.5

Compare Gemini 3 Pro and Kimi K2.5 side-by-side. See how these vision models stack up in OCR, Image Captioning, and Open Prompt.

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GoogleGemini 3 Pro

Gemini 3 Pro is deprecated and can no longer be run. Details and evals are still available on its model page.

MoonshotAIKimi K2.5
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Models in this comparison

MoonshotAI

Gemini 3 Pro vs Kimi K2.5 Comparison Table

Evals updated August 27, 2026Pricing updated August 30, 2026

PropertyGemini 3 ProKimi K2.5
OrganizationGoogleMoonshot AI
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateNov 2025Jan 2026
Context Window1.0M256K
Parameters1T
LicenseProprietaryModified MIT
Pricing per 1M tokens
Input $/1M$0.600
Output $/1M$3.00
Vision Tasks
CaptioningDemo
Chart Question Answering
Classification
Document Question Answering
Image Tagging
Multi-Label Classification
OCRDemo
Vision Language
Visual Question AnsweringDemo
Object Detection
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision

Gemini 3 Pro vs Kimi K2.5: Overview

Gemini 3 Pro

Gemini 3 Pro is Google DeepMind’s flagship multimodal frontier model, built for high-accuracy reasoning and large-scale context understanding across text, images, audio, video, code, and documents. It delivers major gains over Gemini 2.5 Pro, supported by a 1M-token window and strong performance on Google-reported benchmarks such as GPQA Diamond, MMMU-Pro, and Video-MMMU.

The model excels at structured outputs, tool use, and agentic coding, enabling complex multi-step workflows and analysis of entire books, codebases, or long videos in a single prompt. Positioned as Google’s top production model, it balances advanced reasoning with broad multimodal capabilities, making it well suited for research assistants, automation agents, coding systems, and enterprise-scale document and media analysis.

Kimi K2.5

Kimi K2.5 is a frontier-scale multimodal AI model developed by Moonshot AI and released on January 27, 2026. As a significant advancement within the Kimi K2 family, it utilizes a sparse Mixture-of-Experts (MoE) architecture with 1 trillion total parameters (32 billion active per inference) and a massive 256K-token context window. The model features native multimodal integration via a 400M-parameter MoonViT encoder, allowing it to process text, images, and video frames simultaneously. Built for both speed and depth, it offers "Instant" and "Thinking" modes, the latter of which excels at expert-level reasoning, scoring 50.2% on the Humanity’s Last Exam (HLE) benchmark when equipped with tools.

The model is released under a Modified MIT License, which remains open-weight but requires attribution for high-revenue commercial entities. It introduces an "Agent Swarm" paradigm capable of coordinating up to 100 specialized sub-agents for parallel workflows, significantly reducing latency in complex research tasks. For vision tasks, Kimi K2.5 demonstrates strong autonomous visual debugging capabilities, where it can inspect its own generated UI outputs against visual specifications to iteratively refine frontend code. This makes it a powerful choice for developers testing automated UI reconstruction, high-fidelity OCR document processing, and multi-step agentic research grounded in complex visual data.

Frequently Asked Questions

Gemini 3 Pro is released under Proprietary, while Kimi K2.5 uses Modified MIT. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.

Yes. The comparison demo on this page runs both models on the same image side by side for OCR and image captioning in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.