Fully-managed Llama models
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Llama models are available for use as managed APIs and self-deployed
models on Gemini Enterprise Agent Platform. You can stream your responses to reduce the
end-user latency perception. A streamed response uses server-sent events (SSE)
to incrementally stream the response.
Managed Llama models
Llama models offer fully managed and serverless models as APIs. To
use a Llama model on Agent Platform, send a request directly
to the Agent Platform API endpoint. When using Llama models as a
managed API, there's no need to provision or manage infrastructure.
The following models are available from Llama to use in
Gemini Enterprise Agent Platform. To access a Llama model, go to its
Model Garden model card.
Llama 4 Maverick 17B-128EThe largest and most capable multimodal Llama 4 model (MoE 17B active / 400B total), optimized for coding, deep reasoning, sophisticated chat, and high-precision image understanding.Llama 4 Scout 17B-16EHigh-efficiency MoE model (17B active / 109B total) delivering state-of-the-art results for long-context retrieval, document summarization, and reasoning across large codebases.blockLlama 3.3 70BA text-only 70B instruction-tuned model that provides enhanced performance relative to Llama 3.1 70B and Llama 3.2 90B for text-only applications.
Use Llama models
For managed models, you can use curl commands to send requests to the
Gemini Enterprise Agent Platform endpoint using the following model names. To learn how to make
streaming and non-streaming calls to Llama
models, see Call open model
APIs.
To use a self-deployed Gemini Enterprise Agent Platform model:
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2026-09-25 UTC."],[],[]]