Gemini 2.5 Flash Vision
Gemini 2.5 Flash Vision is Google's vision model offering a 1,048,576-token context window with real-time latency.
GoogleFast multimodal vision with massive context
Gemini 2.5 Flash Vision is a vision-capable language model developed by Google, released in June 2025 under the Gemini 2.5 Flash family. It accepts image inputs alongside text and is designed to process and reason over visual content at low latency, making it suitable for applications that require quick turnaround on image-based queries. The model supports a context window of 1,048,576 tokens, which allows it to handle long documents, multiple images, or extended conversations within a single request.
Gemini 2.5 Flash Vision is well-suited for tasks such as image description, visual question answering, document analysis with embedded visuals, and multimodal data extraction. Its combination of a large context window and real-time latency characteristics makes it a practical choice for developers building interactive or high-throughput applications. The model is available through MindStudio without requiring separate API key management, and it supports configurable temperature and maximum response token settings to tune output behavior.
What Gemini 2.5 Flash Vision supports
Large Context Window
Processes up to 1,048,576 tokens in a single request, enabling analysis of long documents, extended conversations, or multiple images at once.
Real-Time Latency
Designed for low-latency responses, making it suitable for interactive applications and high-throughput pipelines that require fast turnaround.
Visual Understanding
Accepts image inputs alongside text to support tasks like image description, visual question answering, and document analysis with embedded visuals.
Configurable Output
Exposes temperature and max response token controls, allowing developers to tune response creativity and length up to 65,535 tokens per response.
Multimodal Reasoning
Combines text and image understanding to reason across mixed-modality inputs, supporting use cases like chart interpretation and visual data extraction.
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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 long inputs including multiple images and extended text within a single request.
What is the maximum response length?
The model can generate responses up to 65,535 tokens in length, which is configurable via the Max Response Tokens input.
What types of inputs does this model accept?
The model is classified as a vision model and accepts image and text inputs. Configurable parameters include temperature and maximum response tokens.
What is the pricing for Gemini 2.5 Flash Vision on MindStudio?
Pricing information is not published in the available metadata. You can check MindStudio's pricing page or the model's detail page for current cost information.
What is the knowledge cutoff date for Gemini 2.5 Flash Vision?
The metadata does not specify a knowledge cutoff date. The model was released in June 2025; refer to Google's official documentation for the exact training data cutoff.
Do I need an API key to use this model on MindStudio?
No. Gemini 2.5 Flash Vision is available as a first-party model on MindStudio, so no separate API key is required to use it within the platform.
Parameters & options
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