> ## Documentation Index
> Fetch the complete documentation index at: https://documentation.deepmask.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Gemini 2.5 Flash & Pro 

> Explore Gemini 2.5 Flash and 2.5 Pro on DeepMask. From high-throughput multimodal processing to deep reasoning, both models offer a 1M+ token context window.

Google's Gemini models bring two distinct capabilities to your DeepMask workspace: Gemini 2.5 Flash delivers high-throughput, low-cost multimodal processing at scale, while Gemini 2.5 Pro applies a native "Thinking" architecture to tackle complex reasoning, coding, and research tasks. Both models share a massive context window and full multimodal support for text, images, video, and audio.

<Tabs>
  <Tab title="Gemini 2.5 Flash">
    ## About

    Gemini 2.5 Flash is Google's most efficient multimodal model, engineered for scale. It provides a massive 1-million-token context window at a fraction of the cost of Pro-tier models, and is specifically optimized for high-volume tasks such as real-time video summarization, large-scale document OCR, and high-speed data extraction. It is the most cost-effective way to process native audio and video inputs via API.

    <Note>
      Gemini 2.5 Flash is served via Google's infrastructure. Your data is processed under DeepMask's EU data-handling agreements.
    </Note>

    ## Key Capabilities

    <CardGroup cols={2}>
      <Card title="Long-Context Retrieval" icon="magnifying-glass">
        Maintains near-perfect accuracy (99%+) when finding specific data points across a million tokens.
      </Card>

      <Card title="Native Audio/Video Understanding" icon="film">
        Processes video at 1 frame per second and audio at 16 kHz for high-fidelity temporal reasoning.
      </Card>

      <Card title="Context Caching" icon="database">
        Store massive datasets — such as a 100-video training course — for rapid, cost-efficient recurring queries.
      </Card>

      <Card title="Real-Time Multimodal" icon="bolt">
        Supports real-time, low-latency multimodal interactions for voice assistants and live monitoring pipelines.
      </Card>
    </CardGroup>

    ## Use Cases

    * **Real-time customer support** — Power conversational bots that can understand user-uploaded screenshots or voice notes instantly.
    * **Large-scale document synthesis** — Summarize hundreds of PDFs or hour-long meeting recordings in a single pass.
    * **Multimodal agents** — Build assistants that can navigate your data across Gmail, Photos, and Workspace to perform complex cross-app tasks.
    * **High-speed data extraction** — Process and reformat massive structured or semi-structured datasets with high throughput.

    <Tip>
      Use Gemini 2.5 Flash when you need to process large volumes of multimodal content at low cost. For complex reasoning or tasks requiring step-by-step logic, switch to Gemini 2.5 Pro.
    </Tip>

    ## Specifications

    | Specification    | Value                                                           |
    | ---------------- | --------------------------------------------------------------- |
    | Model Provider   | Google                                                          |
    | Main Use Cases   | Data Extraction, Real-time Summarization, Large Codebase Search |
    | Reasoning Effort | Adaptive (Balanced)                                             |
    | GPQA Diamond     | 68.3%                                                           |
    | Max Context      | 1.04M Tokens                                                    |
    | Latency (TTFT)   | 0.15s                                                           |
    | Throughput       | 185 Tokens/sec                                                  |
  </Tab>

  <Tab title="Gemini 2.5 Pro">
    ## About

    Gemini 2.5 Pro is Google's most advanced reasoning model. Unlike the Flash variant, which prioritizes speed, the Pro model is engineered for "Thinking" — an internal process where it explores multiple solutions and verifies its own logic before responding. It features a standardized 1-million-token context window (scalable to 2M for select enterprise tiers) and is the primary model behind Deep Research and Agentic Coding workflows in the Gemini ecosystem.

    <Note>
      Gemini 2.5 Pro is served via Google's infrastructure. Your data is processed under DeepMask's EU data-handling agreements.
    </Note>

    ## Key Capabilities

    <CardGroup cols={2}>
      <Card title="Native Thinking Architecture" icon="brain">
        Built-in chain-of-thought reasoning lets the model pause and plan for complex queries without needing specialized prompts.
      </Card>

      <Card title="Massive Repository Reasoning" icon="code">
        Ingests over 30,000 lines of code or 1,500 pages of text while maintaining perfect needle-in-a-haystack recall.
      </Card>

      <Card title="Computer Use" icon="desktop">
        Leverages visual reasoning to interact with web browsers and software UIs, performing multi-step administrative tasks autonomously.
      </Card>

      <Card title="High-Fidelity Multimodal" icon="image">
        Processes up to 3,000 images, 1 hour of video, or 8 hours of audio simultaneously to find cross-modal patterns.
      </Card>
    </CardGroup>

    ## Use Cases

    * **Autonomous software engineering** — Debug and refactor entire code repositories by understanding full project architecture, not just individual functions.
    * **Deep research and strategy** — Synthesize dozens of academic papers or financial reports into a comprehensive, cited brief.
    * **Enterprise decision support** — Analyze dense legal contracts or medical records to identify subtle risks that smaller models might miss.
    * **Personal intelligence** — Act as a proactive agent that manages your Google Workspace (Gmail, Docs, Drive) to organize schedules and complex data.

    <Tip>
      Use Gemini 2.5 Pro when accuracy and multi-step reasoning matter more than cost. Its Thinking architecture makes it ideal for tasks where you need the model to verify its own logic before responding.
    </Tip>

    ## Specifications

    | Specification    | Value                                        |
    | ---------------- | -------------------------------------------- |
    | Model Provider   | Google                                       |
    | Main Use Cases   | Professional Coding, Agentic Browser Control |
    | Reasoning Effort | High                                         |
    | GPQA Diamond     | 84.4%                                        |
    | Max Context      | 1.04M – 2.0M Tokens                          |
    | Latency (TTFT)   | 0.45s                                        |
    | Throughput       | 128 Tokens/sec                               |
  </Tab>
</Tabs>