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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Gemini 3.1 Pro vs Kimi K2.5 Comparison Table
Evals updated September 3, 2026Pricing updated September 4, 2026
| Property | Gemini 3.1 Pro | Kimi K2.5 |
|---|---|---|
| Organization | Moonshot AI | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Jan 2026 |
| Context Window | 1.0M | 256K |
| Parameters | 1T | |
| License | Proprietary | Modified MIT |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $0.450 |
| Output $/1M | $12.00 | $2.25 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Object Detection | Demo | |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 83.3% | Not evaluated |
| Avg cost / sample | $0.0093 | – |
| Avg speed / sample | 7.81s | – |
| By task | ||
| Object Detection | 67.4% | – |
| Counting | 71.6% | – |
| Identification | 100.0% | – |
| OCR | 92.6% | – |
| Data Extraction | 95.9% | – |
| Reasoning (low) | 72.2% | – |
| Reasoning (high) | 74.8% | – |
Gemini 3.1 Pro vs Kimi K2.5: Overview
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 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.