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Gemini 3.1 Pro vs Kimi K2.5

Compare Gemini 3.1 Pro and Kimi K2.5 side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, and OCR.

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GoogleGemini 3.1 Pro
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MoonshotAIKimi K2.5
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Models in this comparison

MoonshotAI

Gemini 3.1 Pro vs Kimi K2.5 Comparison Table

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

PropertyGemini 3.1 ProKimi K2.5
OrganizationGoogleMoonshot AI
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateFeb 2026Jan 2026
Context Window1.0M256K
Parameters1T
LicenseProprietaryModified MIT
Pricing per 1M tokens
Input $/1M$2.00$0.570
Output $/1M$12.00$2.85
Vision Tasks
CaptioningDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
ClassificationDemo
Object DetectionDemo
Model Features
Multimodal Vision
Foundation Vision
LLMs with Vision Capabilities
Vision Evalsground-truth scores across 6 vision tasks
Overall
84.6%
Not evaluated
Object Detection
56.9%
Counting
71.6%
Identification
100.0%
OCR
92.6%
Data Extraction
94.8%
Reasoning
91.3%
Avg cost / sample$0.0068
Avg speed / sample5.9s

Gemini 3.1 Pro vs Kimi K2.5: Overview

Gemini 3.1 Pro

Gemini 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.

The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.

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

Kimi K2.5 has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.

Gemini 3.1 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 image captioning and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.