> ## Documentation Index > Fetch the complete documentation index at: https://agno-v2-agui.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Metrics > Token usage, timing, and per-model breakdown for runs, messages, sessions, and tool calls. | Class | Used On | Purpose | | ----------------- | -------------------------------------------- | ----------------------------------------- | | `RunMetrics` | `RunOutput.metrics`, `TeamRunOutput.metrics` | Run-level totals with per-model breakdown | | `MessageMetrics` | `Message.metrics` | Per-API-call tokens and timing | | `SessionMetrics` | `agent.get_session_metrics()` | Aggregated across all runs in a session | | `ModelMetrics` | Inside `RunMetrics.details` | Per-model aggregate by `(provider, id)` | | `ToolCallMetrics` | `ToolExecution.metrics` | Tool execution timing | All metric classes except `ToolCallMetrics` 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 of the API call(s). | ## RunMetrics Used on `RunOutput.metrics` and `TeamRunOutput.metrics`. Includes all `BaseMetrics` fields plus: | Parameter | Type | Default | Description | | --------------------- | ----------------------------------------- | ------- | ---------------------------------------------------------------------------------------------- | | `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 | | `"culture_model"` | Culture 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"`. `Metrics` is preserved as a backward-compatible alias for `RunMetrics`. Both `from agno.metrics import Metrics` and `from agno.models.metrics import Metrics` still work. ## MessageMetrics Used on `Message.metrics`. Per-API-call metrics. Includes all `BaseMetrics` fields plus: | Parameter | Type | Default | Description | | --------------------- | -------------------------- | ------- | ----------------------------------------------------------------- | | `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()`. 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 | | ------------ | ----------------- | ------- | ------------------------------------------ | | `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). | ## Provider field availability Not all providers populate all fields. 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`.