Gemini 2.5 Flash Vision
Gemini 2.5 Flash is a thinking model that offers great, well-rounded capabilities. It is designed to offer a balance between price and performance.
Google Multimodal vision with large context and fast latency
Gemini 2.5 Flash Vision is a multimodal vision model developed by Google, designed to process and reason over visual inputs alongside text. It is part of the Gemini 2.5 Flash family, which is built around balancing cost efficiency with broad capability coverage. The model supports a context window of 1,048,576 tokens, making it suitable for tasks that require processing large amounts of information in a single request. It was trained with a knowledge cutoff of June 2025.
This model is positioned for use cases where real-time or low-latency responses are important, such as visual question answering, document analysis with images, and applications that combine vision with extended context. The "thinking" architecture underlying the Gemini 2.5 Flash series enables the model to apply multi-step reasoning before producing a response. Developers looking for a vision-capable model that can handle long documents, images, and mixed-modality inputs without incurring the cost of larger models will find this a practical option.
What Gemini 2.5 Flash Vision supports
Large Context Window
Supports up to 1,048,576 tokens in a single context, enabling processing of long documents, extended conversations, or large batches of visual and textual content.
Real-Time Latency
Optimized for low-latency responses, making it suitable for interactive applications and real-time visual analysis workflows.
Visual Understanding
Processes image inputs alongside text to answer questions, describe scenes, extract information, or reason over visual content.
Multimodal Reasoning
Applies multi-step thinking across both visual and textual inputs, supporting tasks like document comprehension that combine images and text.
Structured Output
Can return responses in structured formats, useful for extracting data from images or documents into machine-readable outputs.
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Get Started FreeBenchmark scores
Scores represent accuracy — the percentage of questions answered correctly on each test.
| Benchmark | What it tests | Score |
|---|---|---|
| MMLU-Pro | Expert knowledge across 14 academic disciplines | 80.9% |
| GPQA Diamond | PhD-level science questions (biology, physics, chemistry) | 68.3% |
| MATH-500 | Undergraduate and competition-level math problems | 93.2% |
| AIME 2024 | American math olympiad problems | 50.0% |
| LiveCodeBench | Real-world coding tasks from recent competitions | 49.5% |
| HLE | Questions that challenge frontier models across many domains | 5.1% |
| SciCode | Scientific research coding and numerical methods | 29.1% |
Common questions about Gemini 2.5 Flash Vision
What is the context window size for Gemini 2.5 Flash Vision?
Gemini 2.5 Flash Vision supports a context window of 1,048,576 tokens, allowing very large amounts of text and visual content to be processed in a single request.
What is the knowledge cutoff date for this model?
The model has a training data cutoff of June 2025, as indicated in the model metadata.
What input types does Gemini 2.5 Flash Vision support?
The model is classified as a Vision type and is designed to accept image inputs alongside text, enabling multimodal tasks.
Is this model suitable for latency-sensitive applications?
Yes. Gemini 2.5 Flash Vision is tagged for real-time latency, meaning it is optimized to return responses quickly, which is relevant for interactive or production applications.
Who publishes Gemini 2.5 Flash Vision?
The model is published by Google and is part of the Gemini 2.5 Flash model family, available through Google's AI infrastructure including Vertex AI.
Parameters & options
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