GPT-5.4 Mini vs Qwen3.7 Plus
Compare GPT-5.4 Mini and Qwen3.7 Plus side-by-side. See how these vision models stack up in Open Prompt, Object Detection, Classification, Image Captioning, and OCR.
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Models in this comparison
GPT-5.4 Mini vs Qwen3.7 Plus on Vision Evals
GPT-5.4 Mini scores higher on 3 of the six Vision Evals tasks.
The widest gap is Object Detection, where Qwen3.7 Plus leads 60.1% to 16.1%.
Overall, GPT-5.4 Mini averages 63.5% (#27 of 31) against 67.4% (#18 of 31) for Qwen3.7 Plus.
Qwen3.7 Plus is cheaper ($0.0008 vs $0.0030 per sample), while GPT-5.4 Mini is faster (5.3s vs 7.0s per sample).
GPT-5.4 Mini vs Qwen3.7 Plus Comparison Table
Evals updated August 20, 2026Pricing updated August 24, 2026
| Property | GPT-5.4 Mini | Qwen3.7 Plus |
|---|---|---|
| Organization | OpenAI | Qwen |
| Category | closed | closed |
| Modality | multimodal | — |
| Release Date | Mar 2026 | — |
| Context Window | 400K | — |
| Parameters | ||
| License | Proprietary | |
| Pricing per 1M tokens | ||
| Input $/1M | $0.750 | $0.320 |
| Output $/1M | $4.50 | $1.28 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | Demo |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Visual Question Answering | Demo | Demo |
| Chart Question Answering | ||
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Vision Language | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 63.5% | 67.4% |
| Avg cost / sample | $0.0030 | $0.0008 |
| Avg speed / sample | 5.35s | 7.01s |
| By task | ||
| Object Detection | 16.1% $0.0044 | 60.1% $0.0013 |
| Counting | 60.8% $0.0019 | 50.0% $0.0004 |
| Identification | 78.1% $0.0013 | 84.4% $0.0003 |
| OCR | 88.1% $0.0042 | 86.5% $0.0009 |
| Data Extraction | 82.5% $0.0014 | 83.5% $0.0004 |
| Reasoning (low) | 55.6% $0.0023 | 39.7% $0.0003 |
| Reasoning (high) | 62.9% $0.0081 | 68.2% $0.0043 |
GPT-5.4 Mini vs Qwen3.7 Plus: Overview
GPT-5.4 mini is a fast, cost-efficient model developed by OpenAI and released on March 17, 2026, optimized for high-throughput workloads and subagent orchestration. It supports text and image inputs within a 400,000-token context window, making it ideal for processing extensive visual datasets and large codebases in a single request. Designed for low-latency production environments, the model integrates with key API features including function calling, web search, and tool-based computer use, allowing it to assist in automated workflows that require navigating digital interfaces.
Compared to the previous GPT-5 mini, this version runs more than twice as fast while approaching the performance levels of the flagship GPT-5.4 on reasoning and coding benchmarks. While the larger GPT-5.4 introduces native, state-of-the-art computer-use capabilities, GPT-5.4 mini provides a scalable alternative for interpreting screenshots and reasoning over dense UI layouts. For vision tasks on Playground, it excels at extracting structured information from visual documents and assisting in agentic tasks that involve real-time interpretation of software interfaces alongside text.
Frequently Asked Questions
On Roboflow's Vision Evals, Qwen3.7 Plus performed slightly better overall. The two split the six vision tasks 3 to 3, but Qwen3.7 Plus averages 67.4% (#18 of 31) against 63.5% (#27 of 31) for GPT-5.4 Mini. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Object Detection benchmark, Qwen3.7 Plus leads with 60.1% against 16.1%. This is the widest gap between the two models across the benchmark's tasks.
Qwen3.7 Plus is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0008 per sample against $0.0030. GPT-5.4 Mini is priced at $0.75 per 1M input tokens and $4.50 per 1M output; Qwen3.7 Plus is priced at $0.32 per 1M input tokens and $1.28 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
GPT-5.4 Mini is faster. Across Roboflow's Vision Evals it averaged 5.3s per inference against 7.0s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.
Yes. The comparison demo on this page runs both models on the same image side by side for open prompts and object detection in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.