Gemini 3 Flash vs GPT-5.5
Compare Gemini 3 Flash and GPT-5.5 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-5.5 on Vision Evals
Gemini 3 Flash scores higher on 4 of the six Vision Evals tasks.
The widest gap is Object Detection, where Gemini 3 Flash leads 39.3% to 13.8%.
Overall, Gemini 3 Flash averages 77.2% (#4 of 16) against 71.8% (#8 of 16) for GPT-5.5.
Gemini 3 Flash is both cheaper ($0.0017 vs $0.021 per sample) and faster (3.9s vs 10.4s per sample).
Gemini 3 Flash vs GPT-5.5 Comparison Table
Evals updated July 10, 2026Pricing updated July 21, 2026
| Property | Gemini 3 Flash | GPT-5.5 |
|---|---|---|
| Organization | OpenAI | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Dec 2025 | Apr 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.500 | $5.00 |
| Output $/1M | $3.00 | $30.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | Demo |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
| Foundation Vision | ||
Vision Evalsground-truth scores across 6 vision tasks | ||
| Overall | 77.2% | 71.8% |
| Object Detection | 39.3% | 13.8% |
| Counting | 67.6% | 64.9% |
| Identification | 93.8% | 90.6% |
| OCR | 87.6% | 91.2% |
| Data Extraction | 96.9% | 87.6% |
| Reasoning | 78.3% | 82.6% |
| Avg cost / sample | $0.0017 | $0.021 |
| Avg speed / sample | 3.9s | 10.4s |
Gemini 3 Flash vs GPT-5.5: 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-5.5 is a multimodal large language model released by OpenAI on April 23, 2026, engineered for autonomous, multi-step knowledge work and agentic workflows. It accepts text, images, and code as input, featuring enhanced spatial reasoning and visual grounding to support its computer use capabilities for operating software and navigating UI elements. Built to execute complex workflows end-to-end, the model interprets loosely defined tasks, selects appropriate tools, and performs self-verification with minimal user intervention. It is available in a standard version, a Thinking mode for extended reasoning budgets, and a Pro variant that uses parallel test-time compute for maximum precision on complex tasks.
Co-optimized with NVIDIA for GB200 NVL72 infrastructure, GPT-5.5 delivers per-token latency comparable to its predecessor GPT-5.4 while maintaining a 1-million-token context window. Despite increased capability, the model achieves greater token efficiency in coding and data analysis workflows, often completing tasks with fewer total tokens than previous versions. OpenAI reports a 60% reduction in hallucination rate compared to GPT-5.4, improving reliability for accuracy-sensitive applications. API access is available via the Responses and Chat Completions endpoints at $5 per million input tokens and $30 per million output tokens, double the unit price of GPT-5.4.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3 Flash performed better. It scores higher on 4 of the six vision tasks and averages 77.2% (#4 of 16) against 71.8% (#8 of 16) for GPT-5.5. 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 3 Flash leads with 39.3% against 13.8%. 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 $0.0017 per sample against $0.021. Gemini 3 Flash is priced at $0.50 per 1M input tokens and $3.00 per 1M output; GPT-5.5 is priced at $5.00 per 1M input tokens and $30.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Gemini 3 Flash is faster. Across Roboflow's Vision Evals it averaged 3.9s per inference against 10.4s. 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.