Gemini 3.1 Pro vs Grok 4
Compare Gemini 3.1 Pro and Grok 4 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 Grok 4: 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.
Grok 4, released by xAI on July 9, 2025, is the fourth-generation model in the Grok family and the most advanced to date. It is multimodal, supporting text, vision, tool use, and real-time web search, with a reported 256,000-token context window for long-form reasoning and document analysis. Its training data extends through November 2024, making it the most up-to-date Grok model at launch.
The lineup includes Grok 4 Generalist for broad tasks, Grok 4 Heavy for higher-capacity reasoning, and Grok 4 Code optimized for programming and debugging. A notable feature is its always-on “Think” mode, designed for deeper multi-step reasoning. While xAI has not disclosed parameter counts, Grok 4 is positioned to compete with frontier models like GPT-5 and Claude 4, balancing real-time knowledge via web integration with structured tool use. It is best suited for coding, complex reasoning, and multimodal AI assistants.
Gemini 3.1 Pro vs Grok 4 Comparison Table
| Property | Gemini 3.1 Pro | Grok 4 |
|---|---|---|
| Organization | xAI | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Jul 2025 |
| Context Window | 1.0M | 256K |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | |
| Output $/1M | $12.00 | |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | |
| Object Detection | Demo | |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalspass/fail results · 66 prompts Score key:≥75%40–74%<40% | ||
| Visual Understanding | ||
| Overall Score | 75.76% | 52.24% |
| Avg Response Time | 6.13s | 85.24s |
| Median input tokensincl. image tokens | 1.1K | |
| Median output tokens | 11 | |
| Est. cost / taskon this benchmark | $0.0024 | |
| Defect Detection | 73.3%(11/15) | 80%(12/15) |
| Document Understanding | 88.9%(8/9) | 44.4%(4/9) |
| Object Counting | 44.4%(4/9) | 10%(1/10) |
| Object Understanding | 92.9%(13/14) | 57.1%(8/14) |
| Spatial Understanding | 73.7%(14/19) | 52.6%(10/19) |
| OCR | ||
| Overall Score | 89.52% | |
| Avg Response Time | 3.11s | |
| Median input tokensincl. image tokens | 1.1K | |
| Median output tokens | 12 | |
| Est. cost / taskon this benchmark | $0.0024 | |
| Focused Scene OCR | 94.9%(94/99) | |
| Handwritten Math | 90%(9/10) | |
| License Plate Recognition | 90%(27/30) | |
| Text Recognition | 86.7%(26/30) | |
| VQA & Extraction | 81.7%(49/60) | |
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