GPT-5 Mini vs Qwen-VL
Compare GPT-5 Mini and Qwen-VL side-by-side.
Compare GPT-5 Mini vs Qwen-VL live
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Models in this comparison
GPT-5 Mini vs Qwen-VL: Overview
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.
Qwen-VL is a large vision-language model released in August 2023 by the Qwen team at Alibaba Cloud. Built on the 7-billion-parameter Qwen language model with an added visual receptor based on Openclip ViT-bigG, the model accepts images, text, and bounding box coordinates as inputs, and can produce both text and bounding boxes as outputs. Qwen-VL processes images at 448×448 resolution, higher than the 224×224 input used by many contemporaneous vision-language models, which supports finer-grained visual recognition and text-heavy tasks such as OCR. This design supports a range of multimodal tasks in a single model, including image captioning, visual question answering, visual grounding, text recognition, and image-conditioned dialogue, with native support for English, Chinese, and multilingual conversation.
At release, Qwen-VL achieved competitive results against contemporaneous vision-language models across zero-shot captioning, general VQA, text-oriented VQA, and referring expression comprehension benchmarks. A chat-tuned variant, Qwen-VL-Chat, is optimized for interactive use with instruction-following and multi-turn conversation. The model is distributed under the Tongyi Qianwen License, a custom license from Alibaba Cloud with specific terms that should be reviewed prior to commercial use. Qwen-VL is the first generation of Alibaba's open multimodal series and precedes the later Qwen2-VL and Qwen2.5-VL releases.
GPT-5 Mini vs Qwen-VL Comparison Table
| Property | GPT-5 Mini | Qwen-VL |
|---|---|---|
| Organization | OpenAI | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Aug 2025 | Aug 2023 |
| Context Window | 400K | — |
| Parameters | ||
| License | Proprietary | Custom |
| Pricing per 1M tokens | ||
| Input $/1M | $0.250 | |
| Output $/1M | $2.00 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Classification | Demo | |
| Object Detection | Demo | |
| OCR | Demo | |
| Model Features | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
| Foundation Vision | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| 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) | |
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