Metrics

Class	Used On	Purpose
`RunMetrics`	`RunOutput.metrics`, `TeamRunOutput.metrics`	Run-level totals with per-model breakdown
`WorkflowMetrics`	`WorkflowRunOutput.metrics`	Per-executor step metrics and total workflow duration
`StepMetrics`	Inside `WorkflowMetrics.steps`	`RunMetrics` for one agent or team step executor
`MessageMetrics`	`Message.metrics`	Per-API-call tokens and timing
`SessionMetrics`	Agent, team, and workflow `get_session_metrics()` methods	Aggregated across all runs in a session
`ModelMetrics`	Inside `RunMetrics.details`	Per-model aggregate by `(provider, id)`
`ToolCallMetrics`	`ToolExecution.metrics`	Tool execution timing

RunMetrics, MessageMetrics, SessionMetrics, and ModelMetrics inherit from BaseMetrics, which provides the shared token and cost fields.

BaseMetrics

Shared token fields inherited by RunMetrics, MessageMetrics, SessionMetrics, and ModelMetrics.

Parameter	Type	Default	Description
`input_tokens`	`int`	`0`	Tokens in the prompt/input.
`output_tokens`	`int`	`0`	Tokens generated by the model.
`total_tokens`	`int`	`0`	Total tokens used (input + output).
`audio_input_tokens`	`int`	`0`	Audio tokens in the input.
`audio_output_tokens`	`int`	`0`	Audio tokens in the output.
`audio_total_tokens`	`int`	`0`	Total audio tokens.
`cache_read_tokens`	`int`	`0`	Tokens served from cache.
`cache_write_tokens`	`int`	`0`	Tokens written to cache.
`reasoning_tokens`	`int`	`0`	Tokens used for reasoning steps.
`cost`	`Optional[float]`	`None`	Cost supplied by the provider, when available; Agno does not calculate it from a pricing table.

RunMetrics

Used on RunOutput.metrics and TeamRunOutput.metrics. Includes all BaseMetrics fields plus:

Parameter	Type	Default	Description
`timer`	`Optional[Timer]`	`None`	Internal timer that computes `duration` and `time_to_first_token`. Excluded from `to_dict()`.
`time_to_first_token`	`Optional[float]`	`None`	Time from run start to first token (seconds). Set once per run.
`duration`	`Optional[float]`	`None`	Total run time (seconds).
`details`	`Optional[Dict[str, List[ModelMetrics]]]`	`None`	Per-model breakdown keyed by model type (e.g., `"model"`, `"output_model"`, `"memory_model"`).
`additional_metrics`	`Optional[Dict[str, Any]]`	`None`	Extra metrics (e.g., `eval_duration`).

`details` keys

The details dictionary uses model type strings as keys. Each key maps to a list of ModelMetrics objects (one per unique model (provider, id) pair).

Key	Description
`"model"`	Primary agent model
`"output_model"`	Output model for structured output
`"parser_model"`	Parser model
`"memory_model"`	Memory model
`"reasoning_model"`	Reasoning model
`"session_summary_model"`	Session summary model
`"learning_model"`	Learning model
`"compression_model"`	Compression model
`"followup_model"`	Followup model

Eval agent metrics are prefixed with eval_. If an eval agent uses model types "model" and "output_model", the details keys become "eval_model" and "eval_output_model".

Import the current types directly:

from agno.metrics import RunMetrics, MessageMetrics, SessionMetrics, ModelMetrics, ToolCallMetrics
from agno.workflow.types import WorkflowMetrics, StepMetrics

The old Metrics alias and agno.models.metrics module are no longer available. The listed model-type keys are built in; applications can also use custom string keys.

WorkflowMetrics

WorkflowRunOutput.metrics uses WorkflowMetrics. Each entry in steps wraps the RunMetrics produced by an agent or team step executor.

Parameter	Type	Default	Description
`steps`	`Dict[str, StepMetrics]`	Required	Agent and team executor metrics keyed by step name.
`timer`	`Optional[Timer]`	`None`	Internal timer that computes `duration`. Excluded from `to_dict()`.
`duration`	`Optional[float]`	`None`	Total workflow execution time (seconds).

StepMetrics

Parameter	Type	Default	Description
`step_name`	`str`	Required	Step name.
`executor_type`	`str`	Required	Executor type, such as `"agent"` or `"team"`.
`executor_name`	`str`	Required	Executor name.
`metrics`	`Optional[RunMetrics]`	`None`	Run metrics for the step executor.

MessageMetrics

Used on Message.metrics. Per-API-call metrics. Includes all BaseMetrics fields plus:

Parameter	Type	Default	Description
`timer`	`Optional[Timer]`	`None`	Internal timer that computes `duration` and `time_to_first_token`. Excluded from `to_dict()`.
`duration`	`Optional[float]`	`None`	Duration of this API call (seconds).
`time_to_first_token`	`Optional[float]`	`None`	Time to first token for this API call (seconds).
`provider_metrics`	`Optional[Dict[str, Any]]`	`None`	Provider-specific metrics (e.g., Ollama timing, Cerebras timing).

SessionMetrics

Returned by agent.get_session_metrics(), team.get_session_metrics(), and workflow.get_session_metrics(). Aggregated across all runs in a session. Includes all BaseMetrics fields plus:

Parameter	Type	Default	Description
`details`	`Optional[Dict[str, List[ModelMetrics]]]`	`None`	Per-model breakdown, same structure as `RunMetrics.details`. Tokens summed across runs.
`additional_metrics`	`Optional[Dict[str, Any]]`	`None`	Aggregated additional metrics from all runs.

ModelMetrics

Per-model aggregate stored inside RunMetrics.details[model_type]. Includes all BaseMetrics fields plus:

Parameter	Type	Default	Description
`id`	`str`	`""`	Model ID (e.g., `"gpt-4o"`).
`provider`	`str`	`""`	Provider name (e.g., `"OpenAI Chat"`, `"OpenAI Responses"`, `"Anthropic"`).
`provider_metrics`	`Optional[Dict[str, Any]]`	`None`	Provider-specific data for this model.

ToolCallMetrics

Used on ToolExecution.metrics. Standalone class (does not inherit BaseMetrics).

Parameter	Type	Default	Description
`timer`	`Optional[Timer]`	`None`	Internal timer that computes `duration`. Excluded from `to_dict()`.
`start_time`	`Optional[float]`	`None`	Unix timestamp when the tool call started.
`end_time`	`Optional[float]`	`None`	Unix timestamp when the tool call ended.
`duration`	`Optional[float]`	`None`	Tool execution time (seconds).

Not all providers populate all fields. A cost checkmark means the adapter can read a cost value if the response includes one; it does not guarantee that the provider returns it. This table shows which BaseMetrics fields each provider sets on MessageMetrics.

Provider	Standard tokens	`cache_read`	`cache_write`	`reasoning`	Audio tokens	`cost`	`provider_metrics`
OpenAI Chat	✅	✅		✅	✅	✅
OpenAI Responses	✅	✅		✅
Anthropic Claude	✅	✅	✅				`server_tool_use`, `service_tier`
Google Gemini	✅	✅		✅			`traffic_type`
Groq	✅						`completion_time`, `prompt_time`, `queue_time`, `total_time`
Mistral	✅	✅		✅
AWS Bedrock	✅	✅	✅
LiteLLM	✅	✅		✅	✅
Perplexity	✅	✅		✅	✅
Azure AI Foundry	✅	✅		✅
Cerebras	✅						`time_system`, `time_prompt`
Ollama	✅						`total_duration`, `load_duration`, `prompt_eval_duration`, `eval_duration`
Cohere	✅
Meta Llama	✅
Meta Llama (OpenAI)	✅	✅		✅	✅	✅
HuggingFace	✅
IBM WatsonX	✅

"Standard tokens" = input_tokens, output_tokens, total_tokens. "Audio tokens" = audio_input_tokens, audio_output_tokens.