Gemini 3 Flash vs GPT-5.4 Mini
Compare Gemini 3 Flash and GPT-5.4 Mini side-by-side. See how these vision models stack up in Object Detection, Classification, Open Prompt, OCR, and Image Captioning.
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Models in this comparison
Gemini 3 Flash vs GPT-5.4 Mini on Vision Evals
Gemini 3 Flash scores higher on all five Vision Evals tasks.
The widest gap is Object Detection, where Gemini 3 Flash leads 38.6% to 15.8%.
Overall, Gemini 3 Flash averages 65.7% (#25 of 61) against 53.2% (#49 of 61) for GPT-5.4 Mini.
Gemini 3 Flash is cheaper ($0.0024 vs $0.0034 per sample), while GPT-5.4 Mini is faster (5.5s vs 5.8s per sample).
Gemini 3 Flash vs GPT-5.4 Mini Comparison Table
Evals updated October 8, 2026Pricing updated October 10, 2026
| Property | Gemini 3 Flash | GPT-5.4 Mini |
|---|---|---|
| Organization | OpenAI | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Dec 2025 | Mar 2026 |
| Context Window | 1.0M | 400K |
| Parameters | Unknown | Unknown |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.500 | $0.750 |
| Output $/1M | $3.00 | $4.50 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | Supported | Supported |
| Classification | Demo | Demo |
| Document Question Answering | Supported | Supported |
| Image Tagging | Supported | Supported |
| Multi-Label Classification | Supported | Supported |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | Supported | Supported |
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | Supported | Supported |
| LLMs with Vision Capabilities | Supported | Supported |
| Multimodal Vision | Supported | Supported |
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 65.7% | 53.2% |
| Avg cost / sample | $0.0024 | $0.0034 |
| Avg speed / sample | 5.83s | 5.51s |
| By task | ||
| Object Detection (low) | 38.6% | 15.8% ±0.4, Mean of 3 runs, range 15.3 to 16.1 |
| Object Detection (high) | – | 16.6% ±0.8, Mean of 3 runs, range 15.8 to 17.4 |
| Counting (low) | 67.6% | 58.6% ±2.0, Mean of 3 runs, range 56.8 to 60.8 |
| Counting (high) | – | 64.9% ±2.0, Mean of 3 runs, range 63.5 to 67.6 |
| Identification (low) | 93.8% | 83.3% ±1.6, Mean of 3 runs, range 81.3 to 84.4 |
| Identification (high) | – | 82.3% ±3.1, Mean of 3 runs, range 78.1 to 84.4 |
| OCR (low) | 63.9% | 51.1% |
| by category |
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| OCR (high) | 73.1% | 55.8% |
| by category |
|
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| Reasoning (low) | 64.9% | 57.0% ±3.3, Mean of 3 runs, range 54.3 to 60.9 |
| Reasoning (high) | 74.2% | 64.0% ±1.3, Mean of 3 runs, range 62.9 to 65.6 |
Gemini 3 Flash vs GPT-5.4 Mini: Overview
Gemini 3 Flash is a proprietary multimodal large language model developed by Google through Google DeepMind, designed to deliver fast, cost-efficient reasoning across real-time products and developer workflows. Released in December 2025, it is the Flash-tier variant of the Gemini 3 family, balancing low latency with reasoning quality approaching Pro models.
The model supports text, images, audio, and video, with an exceptionally large context window of roughly one million input tokens and outputs up to ~65k tokens. It emphasizes rapid responses for coding, summarization, analysis, and agentic tasks, and exposes configurable “thinking levels” via API to trade speed for deeper reasoning. Today, Gemini 3 Flash positions itself as a high-throughput, production-ready model, serving as the default in the Gemini app and Google Search’s AI Mode, optimized for scalable, interactive AI applications.
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 3 Flash performed better. It scores higher on all five vision tasks and averages 65.7% (#25 of 61) against 53.2% (#49 of 61) 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 at low effort, Gemini 3 Flash leads with 38.6% against 15.8%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 3 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0024 per sample against $0.0034. Gemini 3 Flash is priced at $0.50 per 1M input tokens and $3.00 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 5.5s per inference against 5.8s. 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 image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.