Gemini 2.5 Pro vs GPT-5.4 Mini
Compare Gemini 2.5 Pro and GPT-5.4 Mini side-by-side. See how these vision models stack up in Object Detection, Open Prompt, Classification, OCR, and Image Captioning.
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Models in this comparison
Gemini 2.5 Pro vs GPT-5.4 Mini on Vision Evals
Gemini 2.5 Pro scores higher on 4 of the six Vision Evals tasks.
The widest gap is Object Detection, where Gemini 2.5 Pro leads 26.4% to 3.9%.
Overall, Gemini 2.5 Pro averages 67.9% (#9 of 16) against 65.3% (#14 of 16) for GPT-5.4 Mini.
GPT-5.4 Mini is both cheaper ($0.0026 vs $0.0036 per sample) and faster (4.5s vs 4.7s per sample).
Gemini 2.5 Pro vs GPT-5.4 Mini Comparison Table
Evals updated July 10, 2026Pricing updated July 21, 2026
| Property | Gemini 2.5 Pro | GPT-5.4 Mini |
|---|---|---|
| Organization | OpenAI | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jun 2025 | Mar 2026 |
| Context Window | 1.0M | 400K |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.25 | $0.750 |
| Output $/1M | $10.00 | $4.50 |
| 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 Evalsground-truth scores across 6 vision tasks | ||
| Overall | 67.9% | 65.3% |
| Object Detection | 26.4% | 3.9% |
| Counting | 52.7% | 60.8% |
| Identification | 93.8% | 78.1% |
| OCR | 88.8% | 88.1% |
| Data Extraction | 84.5% | 82.5% |
| Reasoning | 60.9% | 78.3% |
| Avg cost / sample | $0.0036 | $0.0026 |
| Avg speed / sample | 4.7s | 4.5s |
Gemini 2.5 Pro vs GPT-5.4 Mini: Overview
Gemini 2.5 Pro, released on June 17, 2025, is Google DeepMind’s most capable model in the Gemini 2.5 family, optimized for deep reasoning, coding, and complex multimodal tasks. It accepts text, images, audio, video, and PDFs as input and outputs text. The model supports 1 million input tokens with an output capacity of up to 65K tokens, enabling large-scale comprehension of datasets, codebases, and technical documents. Its training knowledge extends to January 2025.
Pro outperforms earlier Gemini 2.0 models across benchmarks, including agentic coding tasks where it achieved ~63.8% on SWE-Bench Verified. It supports structured outputs, function calling, code execution, search grounding, and URL context, making it well-suited for enterprise, STEM, and developer workflows. However, it does not currently support image or audio generation in its stable release, and its higher computational cost and latency make it less efficient than Flash or Flash-Lite. It is available via the Gemini API, Google AI Studio, and Vertex AI.
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, Gemini 2.5 Pro performed better. It scores higher on 4 of the six vision tasks and averages 67.9% (#9 of 16) against 65.3% (#14 of 16) for GPT-5.4 Mini. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Object Detection benchmark, Gemini 2.5 Pro leads with 26.4% against 3.9%. This is the widest gap between the two models across the benchmark's tasks.
GPT-5.4 Mini is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0026 per sample against $0.0036. Gemini 2.5 Pro is priced at $1.25 per 1M input tokens and $10.00 per 1M output; GPT-5.4 Mini is priced at $0.75 per 1M input tokens and $4.50 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 4.5s per inference against 4.7s. 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 object detection and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.