Google Cloud documentation lists Gemini 3.5 Flash as generally available under the model ID gemini-3.5-flash, with multimodal input support, a 1,048,576-token input limit, a 65,535-token output limit, and availability across several billing and deployment options.
Google has documented Gemini 3.5 Flash as a generally available model in its Google Cloud model documentation, identifying it with the model ID gemini-3.5-flash.
Google Cloud Documentation describes Gemini 3.5 Flash as a GA model with support for multimodal inputs. The same documentation lists a maximum input context of 1,048,576 tokens and a maximum output length of 65,535 tokens.
The Google Cloud page also says the model supports PayGo, Flex, Priority, and Batch usage options, and links readers to Google’s pricing information for details on costs. Those deployment and billing references indicate that Google is positioning the model for both interactive and large-scale workloads, though the documentation itself should be the reference point for exact availability and pricing terms.
In a Google Blog post titled “Gemini 3.5: frontier intelligence with action,” Google said it introduced Gemini 3.5 on May 19, 2026, beginning with Gemini 3.5 Flash. According to the blog post, Google described the model as aimed at agentic workflows and coding, and said it would be available through the Gemini app, Search AI Mode, the Gemini API, Antigravity, and enterprise channels.
Google’s wording places Gemini 3.5 Flash within a broader Gemini 3.5 release rather than as a standalone infrastructure update. The blog post frames the model around action-oriented use cases, while the Google Cloud documentation provides the operational details developers and enterprise users need to select the model in production environments.
Google DeepMind’s model card for Gemini 3.5 Flash describes the system as a natively multimodal reasoning model. The model card also lists support for up to a 1 million-token context window and 64,000 output tokens, aligning closely with the more exact token figures shown in Google Cloud Documentation.
The Google DeepMind model card also includes distribution channels, benchmark results, and safety details. Those materials are important because they provide more context than a product documentation page alone: they indicate how Google characterizes the model’s capabilities, where the model is made available, and what safety information Google has chosen to publish alongside the release.
For developers and enterprise teams already using Google’s AI services, the key practical detail is the model identifier: gemini-3.5-flash. That is the name Google Cloud Documentation lists for selecting the model.
The documented input and output limits are also significant. A 1,048,576-token maximum input window allows applications to pass very large bodies of text, code, structured records, or mixed media context into a single request, subject to product limits and pricing. The 65,535-token output ceiling gives applications room for long-form generation, code output, document drafting, or multi-step responses.
At the same time, the published figures do not by themselves establish real-world latency, cost efficiency, or quality across every workload. Teams evaluating Gemini 3.5 Flash should compare Google’s documentation, the Google DeepMind model card, and Google’s pricing page against their own testing requirements.
Google Cloud Documentation now lists Gemini 3.5 Flash as generally available with the model ID gemini-3.5-flash, multimodal input support, a roughly 1 million-token context window, and a roughly 64,000-token output limit. Google’s blog post presents the model as the first Gemini 3.5 release, while Google DeepMind’s model card provides additional information on capabilities, benchmarks, distribution, and safety.
Google has documented Gemini 3.5 Flash as a generally available model in its Google Cloud model documentation, identifying it with the model ID gemini 3.5 flash .
What Google lists for Gemini 3.5 Flash Google Cloud Documentation describes Gemini 3.5 Flash as a GA model with support for multimodal inputs.
The same documentation lists a maximum input context of 1,048,576 tokens and a maximum output length of 65,535 tokens.
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