> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-codex-docs-audit-20260719-0149.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Memory Update Performance Evaluation

> Benchmark agent run latency with update_memory_on_run enabled against a SqliteDb over 5 iterations.

Demonstrates measuring performance when memory updates are enabled.

```python response_with_memory_updates.py theme={null}
"""
Memory Update Performance Evaluation
====================================

Demonstrates measuring performance when memory updates are enabled.
"""

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.eval.performance import PerformanceEval
from agno.models.openai import OpenAIChat

# ---------------------------------------------------------------------------
# Create Database
# ---------------------------------------------------------------------------
db = SqliteDb(db_file="tmp/memory.db")


# ---------------------------------------------------------------------------
# Create Benchmark Function
# ---------------------------------------------------------------------------
def run_agent():
    agent = Agent(
        model=OpenAIChat(id="gpt-5.2"),
        system_message="Be concise, reply with one sentence.",
        db=db,
        update_memory_on_run=True,
    )

    response = agent.run("My name is Tom! I'm 25 years old and I live in New York.")
    print(f"Agent response: {response.content}")

    return response


# ---------------------------------------------------------------------------
# Create Evaluation
# ---------------------------------------------------------------------------
response_with_memory_updates_perf = PerformanceEval(
    name="Memory Updates Performance",
    func=run_agent,
    num_iterations=5,
    warmup_runs=0,
)

# ---------------------------------------------------------------------------
# Run Evaluation
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    response_with_memory_updates_perf.run(print_results=True, print_summary=True)
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno memory-profiler openai sqlalchemy
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run the example">
    Save the code above as `response_with_memory_updates.py`, then run:

    ```bash theme={null}
    python response_with_memory_updates.py
    ```
  </Step>
</Steps>

Full source: [cookbook/09\_evals/performance/response\_with\_memory\_updates.py](https://github.com/agno-agi/agno/blob/v2.7.4/cookbook/09_evals/performance/response_with_memory_updates.py)