GPT-5.2 vs GPT-5 Mini
Compare GPT-5.2 and GPT-5 Mini side-by-side. See how these vision models stack up in Image Captioning, OCR, Object Detection, Open Prompt, and Classification.
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GPT-5.2 vs GPT-5 Mini: Overview
GPT-5.2 is OpenAI’s latest flagship large language model, released in December 2025. It is a proprietary, multimodal system supporting text and vision inputs, along with tool use, and features a 400,000-token context window designed for working with long documents, extended conversations, and complex workflows.
Relative to GPT-5.1, GPT-5.2 is positioned by OpenAI as offering improved long-context reasoning, more capable tool use, and stronger performance on professional tasks such as writing, coding, spreadsheet work, and image interpretation. The model is available in multiple variants (including Instant, Thinking, and Pro) that balance speed, cost, and depth of reasoning, making GPT-5.2 a general-purpose model aimed at reliability and workflow robustness rather than minimal latency or lowest cost.
GPT-5 Mini, released by OpenAI on August 7, 2025, is a mid-tier variant of the GPT-5 family that balances cost, speed, and capability. It is multimodal, supporting both text and image inputs, and offers a substantial input context window of ~400,000 tokens with output lengths up to ~128,000 tokens. While less powerful than the full GPT-5, it inherits its safety tuning, instruction-following improvements, and multimodal reasoning, making it a practical choice for developers who need large context handling without the expense of premium models.
GPT-5 Mini is optimized for affordability while retaining strong reasoning performance. Benchmarks show it outperforming earlier models such as GPT-4o on many multimodal and medical VQA tasks, though it lags behind GPT-5 on the most complex problems. Ideal use cases include prototyping, scalable content generation, document analysis, and mid-range reasoning tasks where efficiency and context capacity matter more than top-tier accuracy.
GPT-5.2 vs GPT-5 Mini Comparison Table
| Property | GPT-5.2 | GPT-5 Mini |
|---|---|---|
| Organization | OpenAI | OpenAI |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Dec 2025 | Aug 2025 |
| Context Window | 400K | 400K |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.75 | $0.250 |
| Output $/1M | $14.00 | $2.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | Demo |
| Object Detection | Demo | 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 · 67 prompts Score key:≥75%40–74%<40% | ||
| Visual Understanding | ||
| Overall Score | 73.13% | |
| Avg Response Time | 11.72s | |
| Median input tokensincl. image tokens | 1.4K | |
| Median output tokens | 143 | |
| Est. cost / taskon this benchmark | $0.0006 | |
| Defect Detection | 80%(12/15) | |
| Document Understanding | 77.8%(7/9) | |
| Object Counting | 10%(1/10) | |
| Object Understanding | 85.7%(12/14) | |
| Spatial Understanding | 89.5%(17/19) | |
| OCR | ||
| Overall Score | 76.86% | |
| Avg Response Time | 4.63s | |
| Median input tokensincl. image tokens | 105 | |
| Median output tokens | 209 | |
| Est. cost / taskon this benchmark | $0.0004 | |
| Focused Scene OCR | 72.7%(72/99) | |
| Handwritten Math | 50%(5/10) | |
| License Plate Recognition | 93.3%(28/30) | |
| Text Recognition | 80%(24/30) | |
| VQA & Extraction | 78.3%(47/60) | |
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