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Gemini 2.5 Flash

Gemini the listed price Flash is part of Google's Gemini the listed price family, which reached general availability on Vertex AI in mid-2025 alongside the larger the listed price Pro model and a lighter the listed price Flash-Lite sibling. Its positioning in the lineup is the speed-and-efficiency tier: it inherits the multimodal and reasoning focus of the the listed price series while being optimized for high-throughput, cost-sensitive enterprise workloads. That makes it a practical fit for production pipelines that need dependable latency and predictable quality on classification, routing, summarization, and structured extraction tasks, rather than the heaviest open-ended reasoning work where the larger Pro tier would be preferable. The model's practical strengths lie in its broad input flexibility and developer-oriented controls, which line up well with Databricks-style data and AI platforms that handle mixed text, document, and media traffic. Teams can lean on it for grounded Q&A over long contexts, automated content transformation, tool-assisted workflows, and generating strictly formatted outputs for downstream systems. Because it sits between the Pro and Flash-Lite siblings, it offers a balanced choice when an application needs more reasoning capability than Flash-Lite can provide but does not require the full depth of Pro, making it a versatile default for many real-world enterprise deployments.

Beyond the base text model, Google later introduced Gemini the listed price Flash Image, a state-of-the-art image-focused variant of the Flash line, signaling continued investment in specialized multimodal capabilities built on the same underlying family. For practitioners choosing the base Flash model on Databricks, the practical takeaway is that they are selecting a production-stable member of Google's 2025 flagship series, with the Flash-Lite sibling serving lighter, higher-volume jobs and the Pro tier reserved for the most demanding reasoning. This tiered design helps teams match model intelligence to workload economics, and the active evolution of the Flash line suggests ongoing improvements in multimodal handling and efficiency that downstream platform offerings are likely to inherit over time.

Databricksdatabricks-gemini-2-5-flashgemini-flash

Quick Info

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Provider
Databricks
Model key
databricks-gemini-2-5-flash
Release date
Jun 17, 2025
Last updated
Jun 17, 2025
Knowledge cutoff
2025-01
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.30
Output token cost
$2.50

Limits

Output tokens
65,536 tokens
Context window
1,048,576 tokens

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