Agent Platform Supported Models and Recommendations

This reference catalog provides technical specifications, tuning recommendations, and deployment hardware requirements for supported models in Agent Platform.

Supported Models Catalog

[!WARNING] CRITICAL AGENT INSTRUCTION Do NOT use this catalog to recommend a specific model to the user until they have explicitly confirmed their Model Category as Open Model. Furthermore, do NOT recommend any model that is not explicitly listed in this catalog, as the tuning service does not support it.

Available open models can be found in Google Cloud documentation. This is the list of open models that are available for tuning; do not suggest any other open models besides the one listed here. Each model has some limitations for tuning.

Model Selection Guidelines

Identify Task: Check a few samples from the dataset to identify the task.

Choose a model family based on your task type:

• Qwen: Best for code generation or complex math-based tasks.
• Gemma: Optimized for chat-based interactions, creative writing and multilingual tasks.
• Llama (Instruct): Strong general-purpose chat/instruction models.
• Llama (Base/Scout): Best for continuation tasks or building custom instruction-tuned models.

Complexity Heuristics:

• Simple (QA, Extraction): 1B - 3B models.
• Intermediate (Summarization, Reasoning): 8B - 17B models.
• Complex (Multi-turn, Tool use, Deep reasoning): 27B - 70B models.

Baseline Hyperparameter Recommendations

These values are starting points and should be adjusted based on your dataset size.