diff --git a/py/model_performance_report.md b/py/model_performance_report.md
new file mode 100644
index 0000000000..f508c18403
--- /dev/null
+++ b/py/model_performance_report.md
@@ -0,0 +1,68 @@
+# Model Performance Test Report
+
+## Summary
+
+- **Total Tests**: 8
+- **Passed**: 8
+- **Failed**: 0
+- **Success Rate**: 100.0%
+
+## Detailed Results
+
+### googleai/gemini-2.0-flash
+
+#### Config: `{}`
+
+- **Status**: ✅ SUCCESS
+- **Timing**: 1.602s
+- **Response**: Aye, 5 doubloons plus 3 more... that be 8 doubloons in total!
+
+
+#### Config: `{"temperature": 0.0}`
+
+- **Status**: ✅ SUCCESS
+- **Timing**: 1.832s
+- **Response**: Ahoy there, matey! 5 + 3 be equal to 8! Shiver me timbers!
+
+
+#### Config: `{"temperature": 2.0}`
+
+- **Status**: ✅ SUCCESS
+- **Timing**: 1.565s
+- **Response**: Arrr, 5 doubloons plus 3 doubloons be equal to 8 doubloons! 
+
+
+#### Config: `{"temperature": 1.0}`
+
+- **Status**: ✅ SUCCESS
+- **Timing**: 1.662s
+- **Response**: Aye, 5 doubloons plus 3 doubloons be 8 doubloons in total! Shiver me timbers!
+
+
+#### Config: `{"topP": 0.0}`
+
+- **Status**: ✅ SUCCESS
+- **Timing**: 1.774s
+- **Response**: Ahoy there, matey! 5 + 3 be equal to 8! Shiver me timbers, that be a fine haul o' doubloons!
+
+
+#### Config: `{"topP": 1.0}`
+
+- **Status**: ✅ SUCCESS
+- **Timing**: 1.651s
+- **Response**: Ahoy there, matey! 5 + 3 be equal to 8! Shiver me timbers!
+
+
+#### Config: `{"topP": 0.5}`
+
+- **Status**: ✅ SUCCESS
+- **Timing**: 1.752s
+- **Response**: Ahoy there, matey! 5 + 3 be equal to 8! Shiver me timbers, that be a fine bit o' arithmetic!
+
+
+#### Config: `{"safetySettings": []}`
+
+- **Status**: ✅ SUCCESS
+- **Timing**: 1.562s
+- **Response**: Aye, 5 doubloons plus 3 doubloons be 8 doubloons, me hearty!
+
diff --git a/py/samples/sample-test/README.md b/py/samples/sample-test/README.md
index 5ea91edac4..031098f098 100644
--- a/py/samples/sample-test/README.md
+++ b/py/samples/sample-test/README.md
@@ -1,35 +1,23 @@
-# Sample Test Utilities
+# Model Performance Testing Tool
 
-Internal testing utilities for Genkit samples. These scripts help developers
-verify that sample flows are working correctly.
+A tool to test model performance across different models and configuration variations.
 
-## Scripts
+## Setup
 
-### `review_sample_flows.py`
+1.  Ensure you have `uv` installed.
+2.  Set your API keys (e.g., `GOOGLE_GENAI_API_KEY`).
 
-Reviews and tests all flows in a sample's `main.py`.
+## Usage
 
-```bash
-# Test all flows in a sample
-cd py
-uv run samples/sample-test/review_sample_flows.py samples/provider-google-genai-hello
-
-# Specify custom output file
-uv run samples/sample-test/review_sample_flows.py samples/provider-google-genai-hello --output results.txt
-```
-
-### `run_single_flow.py`
-
-Runs a single flow from a sample. Used internally by `review_sample_flows.py`.
+Run the tool:
 
 ```bash
-cd py
-uv run samples/sample-test/run_single_flow.py samples/provider-google-genai-hello flow_name --input '{"key": "value"}'
+uv run test_model_performance.py --models googleai/gemini-2.0-flash
 ```
 
-## Output
+## Features
 
-The review script generates a report file with:
-- Summary of successful/failed flows
-- Detailed input/output for each flow
-- Error messages and tracebacks for failures
+-   **Model Discovery**: Automatically finds registered models.
+-   **Config Discovery**: Inspects model schema to find parameters.
+-   **Variations**: Tests min, max, midpoint, and default values.
+-   **Report**: Generates a Markdown report with pass/fail stats and detailed results.
diff --git a/py/samples/sample-test/pyproject.toml b/py/samples/sample-test/pyproject.toml
new file mode 100644
index 0000000000..fd55850ca7
--- /dev/null
+++ b/py/samples/sample-test/pyproject.toml
@@ -0,0 +1,45 @@
+# Copyright 2026 Google LLC
+# SPDX-License-Identifier: Apache-2.0
+
+[project]
+name = "sample-test"
+version = "0.1.0"
+description = "Model Performance Testing Tool"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+    "genkit",
+    "genkit-plugin-google-genai",
+    "genkit-plugin-vertex-ai",
+    "genkit-plugin-google-cloud",
+    "genkit-plugin-amazon-bedrock",
+    "genkit-plugin-anthropic",
+    "genkit-plugin-deepseek",
+    "genkit-plugin-xai",
+    "genkit-plugin-ollama",
+    "genkit-plugin-mistral",
+    "genkit-plugin-evaluators",
+    "fastapi",
+    "uvicorn",
+    "datamodel-code-generator",
+]
+
+[build-system]
+build-backend = "hatchling.build"
+requires      = ["hatchling"]
+
+[tool.hatch.build.targets.wheel]
+packages = ["test_model_performance.py", "run_single_model_test.py"]
+
+[tool.uv.sources]
+genkit = { path = "../../packages/genkit", editable = true }
+genkit-plugin-google-genai = { path = "../../plugins/google-genai", editable = true }
+genkit-plugin-vertex-ai = { path = "../../plugins/vertex-ai", editable = true }
+genkit-plugin-google-cloud = { path = "../../plugins/google-cloud", editable = true }
+genkit-plugin-amazon-bedrock = { path = "../../plugins/amazon-bedrock", editable = true }
+genkit-plugin-anthropic = { path = "../../plugins/anthropic", editable = true }
+genkit-plugin-deepseek = { path = "../../plugins/deepseek", editable = true }
+genkit-plugin-xai = { path = "../../plugins/xai", editable = true }
+genkit-plugin-ollama = { path = "../../plugins/ollama", editable = true }
+genkit-plugin-mistral = { path = "../../plugins/mistral", editable = true }
+genkit-plugin-evaluators = { path = "../../plugins/evaluators", editable = true }
diff --git a/py/samples/sample-test/run_single_model_test.py b/py/samples/sample-test/run_single_model_test.py
new file mode 100644
index 0000000000..dbb8db3e5e
--- /dev/null
+++ b/py/samples/sample-test/run_single_model_test.py
@@ -0,0 +1,163 @@
+#!/usr/bin/env python3
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+"""Helper script to run a single model test in isolation.
+
+This script is called by test_model_performance.py to execute each model+config
+test in a separate subprocess, avoiding state pollution and enabling timeout handling.
+
+Usage:
+    python run_single_model_test.py <model_name> --config <json_config> --user-prompt <text> --system-prompt <text>
+
+Output:
+    JSON object with 'success', 'response', 'error', 'timing' fields
+"""
+
+import argparse
+import json
+import sys
+import time
+from typing import Any
+
+
+async def run_model_test(
+    model_name: str,
+    config: dict[str, Any],
+    user_prompt: str,
+    system_prompt: str | None = None,
+) -> dict[str, Any]:
+    """Run a single model test and return result.
+
+    Args:
+        model_name: Name of the model to test
+        config: Configuration dictionary for the model
+        user_prompt: User prompt to send
+        system_prompt: Optional system prompt
+
+    Returns:
+        Dict with 'success', 'response', 'error', 'timing' fields
+    """
+    result: dict[str, Any] = {
+        "success": False,
+        "response": None,
+        "error": None,
+        "timing": 0.0,
+    }
+
+    try:
+        # Import Genkit
+        from genkit import Genkit
+        from genkit.plugins.google_genai import GoogleAI, VertexAI
+        from genkit.core.typing import Message, TextPart
+
+        plugins = []
+        try:
+            plugins.append(GoogleAI())
+        except Exception:
+            pass
+        try:
+            plugins.append(VertexAI())
+        except Exception:
+            pass
+
+        # Initialize Genkit
+        ai = Genkit(plugins=plugins)
+
+        # Build the prompt
+        messages = []
+        if system_prompt:
+            messages.append(Message(
+                role='system',
+                content=[TextPart(text=system_prompt)]
+            ))
+        messages.append(Message(
+            role='user',
+            content=[TextPart(text=user_prompt)]
+        ))
+
+        # Start timing
+        start_time = time.time()
+
+        # Run generation
+        response = await ai.generate(
+            model=model_name,
+            messages=messages,
+            config=config,
+        )
+
+        # Calculate timing
+        elapsed = time.time() - start_time
+
+        # Extract response text
+        response_text = response.text if hasattr(response, 'text') else str(response)
+
+        result["success"] = True
+        result["response"] = response_text
+        result["timing"] = round(elapsed, 3)
+
+    except Exception as e:
+        import traceback
+        result["error"] = f"{type(e).__name__}: {e}\n{traceback.format_exc()}"
+
+    return result
+
+
+def main() -> None:
+    """Run a single model test and output JSON result."""
+    parser = argparse.ArgumentParser(description='Run a single model test.')
+    parser.add_argument('model_name', type=str, help='Name of the model to test')
+    parser.add_argument('--config', type=str, default='{}', help='JSON string of model config')
+    parser.add_argument('--user-prompt', type=str, required=True, help='User prompt text')
+    parser.add_argument('--system-prompt', type=str, default=None, help='System prompt text')
+    args = parser.parse_args()
+
+    # Suppress verbose logging
+    import logging
+    logging.basicConfig(level=logging.ERROR)
+    logging.getLogger('genkit').setLevel(logging.ERROR)
+    logging.getLogger('google').setLevel(logging.ERROR)
+
+    # Override input() to prevent blocking
+    import builtins
+    builtins.input = lambda prompt="": "dummy_value"
+
+    result: dict[str, Any] = {"success": False, "response": None, "error": "Unknown initialization error", "timing": 0.0}
+
+    try:
+        # Parse config
+        config = json.loads(args.config)
+
+        # Run test in async context
+        import asyncio
+        result = asyncio.run(run_model_test(
+            args.model_name,
+            config,
+            args.user_prompt,
+            args.system_prompt,
+        ))
+
+    except Exception as e:
+        result = {"success": False, "response": None, "error": f"Initialization failed: {e}", "timing": 0.0}
+
+    # Output JSON result with markers
+    print("---JSON_RESULT_START---")
+    print(json.dumps(result))
+    print("---JSON_RESULT_END---")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/py/samples/sample-test/server.py b/py/samples/sample-test/server.py
new file mode 100644
index 0000000000..29b69b2fb5
--- /dev/null
+++ b/py/samples/sample-test/server.py
@@ -0,0 +1,301 @@
+#!/usr/bin/env python3
+# Copyright 2026 Google LLC
+# SPDX-License-Identifier: Apache-2.0
+
+"""FastAPI backend for Model Performance Tool."""
+
+from fastapi import FastAPI, HTTPException
+from fastapi.staticfiles import StaticFiles
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import HTMLResponse
+from pydantic import BaseModel
+import asyncio
+from typing import Any, List, Dict
+import logging
+from pathlib import Path
+
+# Import tool logic
+from test_model_performance import discover_models, run_model_test, parse_config_schema
+
+app = FastAPI(title="Model Performance Tool")
+
+# CORS for local dev
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# --- Data Models ---
+
+class Scenario(BaseModel):
+    id: str
+    name: str
+    description: str
+    system_prompt: str
+    user_prompt: str
+
+class TestRequest(BaseModel):
+    model: str
+    config: Dict[str, Any]
+    scenario_id: str
+    user_prompt: str
+    system_prompt: str
+
+class TestResult(BaseModel):
+    success: bool
+    response: str | None
+    error: str | None
+    timing: float
+
+# --- Scenarios Discovery ---
+
+async def discover_scenarios() -> List[Scenario]:
+    samples_dir = Path(__file__).parent.parent
+    scenarios = []
+    
+    if not samples_dir.exists():
+        return scenarios
+
+    # Iterate through sample directories
+    for item in sorted(samples_dir.iterdir()):
+        if item.is_dir() and not item.name.startswith(('.', '_')):
+            # Try to read metadata from pyproject.toml
+            pyproject_path = item / "pyproject.toml"
+            name = item.name
+            description = "Genkit sample project"
+            
+            if pyproject_path.exists():
+                try:
+                    import tomllib # type: ignore
+                    with open(pyproject_path, "rb") as f:
+                        data = tomllib.load(f)
+                        project = data.get("project", {})
+                        name = project.get("name", name)
+                        description = project.get("description", description)
+                except Exception:
+                    pass
+            
+            scenarios.append(Scenario(
+                id=item.name,
+                name=name,
+                description=description,
+                system_prompt="You are a pirate.",
+                user_prompt="what is 5 + 3?"
+            ))
+            
+    return scenarios
+
+# We'll fetch SCENARIOS dynamically in the endpoint
+
+# --- Endpoints ---
+
+from fastapi.responses import HTMLResponse, JSONResponse
+
+@app.get("/", response_class=HTMLResponse)
+async def root():
+    logging.info("Root path accessed")
+    static_dir = Path(__file__).parent / "static"
+    index_path = static_dir / "index.html"
+    if not index_path.exists():
+        logging.error(f"index.html not found at {index_path}")
+        return HTMLResponse(content="index.html not found", status_code=404)
+    return HTMLResponse(content=index_path.read_text())
+
+@app.get("/health")
+async def health_check():
+    return {"status": "ok", "message": "Server is running"}
+
+@app.get("/api/scenarios", response_model=List[Scenario])
+async def get_scenarios():
+    return await discover_scenarios()
+
+@app.get("/api/models")
+async def get_models(sample: str | None = None):
+    """Get models available for a specific sample.
+    
+    Args:
+        sample: Sample name to discover models for (e.g., 'google-genai-hello')
+        
+    Returns:
+        List of models with numbering, info, and parsed parameters
+    """
+    try:
+        # Import the discovery function
+        from test_model_performance import discover_models_for_sample, parse_config_schema
+        
+        if sample:
+            logging.info(f"Discovering models for sample: {sample}")
+            models = await discover_models_for_sample(sample)
+        else:
+            logging.info("Discovering all models")
+            from test_model_performance import discover_models
+            models = await discover_models()
+        
+        logging.info(f"Found {len(models)} models: {list(models.keys())}")
+        
+        # Build numbered model list
+        filtered_models = []
+        for idx, (name, info) in enumerate(models.items(), start=1):
+            # Validate model name
+            if not name or not isinstance(name, str):
+                logging.warning(f"Invalid model name at index {idx}: {name}")
+                continue
+                
+            # Extract config schema for UI
+            config_schema = info.get('customOptions', {}) if isinstance(info, dict) else {}
+            params = parse_config_schema(config_schema)
+            
+            model_entry = {
+                "number": idx,
+                "name": name,
+                "display_name": f"{idx}. {name}",
+                "info": info if isinstance(info, dict) else {},
+                "params": params
+            }
+            
+            logging.debug(f"Model entry: {model_entry['display_name']}")
+            filtered_models.append(model_entry)
+        
+        logging.info(f"Returning {len(filtered_models)} filtered models")
+        return filtered_models
+    except Exception as e:
+        logging.error(f"Error discovering models: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.post("/api/run", response_model=TestResult)
+async def run_test(request: TestRequest):
+    try:
+        script_path = Path(__file__).parent / "run_single_model_test.py"
+        
+        # Run test in thread pool to not block async loop (subprocess call inside)
+        result = await asyncio.to_thread(
+            lambda: asyncio.run(run_wrapper(
+                request.model,
+                request.config,
+                request.user_prompt,
+                request.system_prompt,
+                script_path
+            ))
+        )
+        
+        return TestResult(
+            success=result.get("success", False),
+            response=str(result.get("response")) if result.get("response") else None,
+            error=result.get("error"),
+            timing=result.get("timing", 0.0)
+        )
+
+    except Exception as e:
+        logging.error(f"Error running test: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+class ComprehensiveTestRequest(BaseModel):
+    sample: str
+    model: str
+    user_prompt: str
+    system_prompt: str
+
+
+class ComprehensiveTestResult(BaseModel):
+    total_tests: int
+    passed: int
+    failed: int
+    results: List[Dict[str, Any]]
+
+
+@app.post("/api/run-comprehensive", response_model=ComprehensiveTestResult)
+async def run_comprehensive_test(request: ComprehensiveTestRequest):
+    """Run comprehensive test with all parameter variations.
+    
+    Tests all config parameter variations:
+    1. First test with all defaults ({})
+    2. Then vary one parameter at a time
+    """
+    try:
+        from test_model_performance import (
+            discover_models_for_sample,
+            parse_config_schema,
+            generate_config_variations,
+            run_model_test
+        )
+        
+        # Get model info
+        models = await discover_models_for_sample(request.sample)
+        if request.model not in models:
+            raise HTTPException(status_code=404, detail=f"Model {request.model} not found in sample {request.sample}")
+        
+        model_info = models[request.model]
+        config_schema = model_info.get('customOptions', {})
+        params = parse_config_schema(config_schema)
+        
+        # Generate variations
+        variations = generate_config_variations(params)
+        
+        # Run all tests
+        script_path = Path(__file__).parent / "run_single_model_test.py"
+        all_results = []
+        
+        for config in variations:
+            result = await asyncio.to_thread(
+                run_model_test,
+                request.model,
+                config,
+                request.user_prompt,
+                request.system_prompt,
+                script_path
+            )
+            
+            all_results.append({
+                "config": config,
+                "success": result.get("success", False),
+                "response": result.get("response"),
+                "error": result.get("error"),
+                "timing": result.get("timing", 0.0)
+            })
+        
+        # Calculate stats
+        passed = sum(1 for r in all_results if r["success"])
+        failed = len(all_results) - passed
+        
+        return ComprehensiveTestResult(
+            total_tests=len(all_results),
+            passed=passed,
+            failed=failed,
+            results=all_results
+        )
+        
+    except HTTPException:
+        raise
+    except Exception as e:
+        logging.error(f"Error running comprehensive test: {e}", exc_info=True)
+        import traceback
+        traceback.print_exc()
+        raise HTTPException(status_code=500, detail=f"Internal Server Error: {str(e)}")
+
+# Wrapper to run async run_model_test inside the thread
+async def run_wrapper(model, config, user_prompt, system_prompt, script_path):
+    # run_model_test in test_model_performance is synchronous (uses subprocess.run)
+    # We need to call it directly. Wait, run_model_test in test_model_performance IS synchronous wrapper around subprocess.
+    # So we don't need asyncio.run inside the lambda unless run_model_test was async.
+    # Checking test_model_performance.py... run_model_test is synchronous.
+    
+    return run_model_test(
+        model,
+        config,
+        user_prompt,
+        system_prompt,
+        script_path
+    )
+
+# Mount static files (CSS, JS, etc.) under /static/
+STATIC_DIR = Path(__file__).parent / "static"
+app.mount("/static", StaticFiles(directory=str(STATIC_DIR)), name="static")
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="127.0.0.1", port=8000)
diff --git a/py/samples/sample-test/static/index.html b/py/samples/sample-test/static/index.html
new file mode 100644
index 0000000000..a165a8436c
--- /dev/null
+++ b/py/samples/sample-test/static/index.html
@@ -0,0 +1,91 @@
+<!DOCTYPE html>
+<html lang="en">
+
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Genkit Model Performance</title>
+    <link rel="preconnect" href="https://fonts.googleapis.com">
+    <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
+    <link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap" rel="stylesheet">
+    <link rel="stylesheet" href="/static/style.css?v=4">
+</head>
+
+<body>
+    <div class="app-container">
+        <!-- Main Content -->
+        <main class="main-content">
+            <header class="top-bar">
+                <div class="brand">
+                    <div class="logo-icon">G</div>
+                    <h1>Genkit Model Config Test</h1>
+                </div>
+                <h2 id="current-scenario-title">Model Performance Testing</h2>
+                <div class="actions">
+                    <span id="model-count" class="badge">0 Models</span>
+                </div>
+            </header>
+
+            <div class="content-grid">
+                <!-- Configuration Column -->
+                <div class="config-panel">
+                    <div class="card">
+                        <h3>Test Configuration</h3>
+
+                        <div class="form-group">
+                            <label>Select Sample</label>
+                            <select id="sample-select">
+                                <option value="">Loading samples...</option>
+                            </select>
+                        </div>
+
+                        <div class="form-group">
+                            <label>Select Model</label>
+                            <select id="model-select">
+                                <option value="">Loading models...</option>
+                            </select>
+                        </div>
+
+                        <div class="form-group">
+                            <label>System Prompt</label>
+                            <textarea id="system-prompt" rows="2"></textarea>
+                        </div>
+
+                        <div class="form-group">
+                            <label>User Prompt</label>
+                            <textarea id="user-prompt" rows="3"></textarea>
+                        </div>
+
+                        <button id="run-btn" class="btn-primary">
+                            Run Test
+                        </button>
+
+                        <button id="run-comprehensive-btn" class="btn-secondary">
+                            Run Comprehensive Test
+                        </button>
+                    </div>
+                </div>
+
+                <!-- Results Column -->
+                <div class="results-panel">
+                    <div class="results-header">
+                        <h3>Results</h3>
+                        <div id="stats-bar" class="hidden">
+                            <span class="stat-item success">Pass: <span id="pass-count">0</span></span>
+                            <span class="stat-item error">Fail: <span id="fail-count">0</span></span>
+                        </div>
+                    </div>
+
+                    <div id="results-list" class="results-list">
+                        <div class="empty-state">
+                            Select a model and run test to see results.
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </main>
+    </div>
+    <script src="/static/script.js?v=3"></script>
+</body>
+
+</html>
\ No newline at end of file
diff --git a/py/samples/sample-test/static/script.js b/py/samples/sample-test/static/script.js
new file mode 100644
index 0000000000..b0f14cff85
--- /dev/null
+++ b/py/samples/sample-test/static/script.js
@@ -0,0 +1,282 @@
+const API_BASE = '/api';
+
+// State
+let currentState = {
+    scenarios: [],
+    models: [],
+    selectedScenarioId: null,
+    selectedModel: null,
+    stats: { pass: 0, fail: 0 }
+};
+
+// DOM Elements
+const els = {
+    sampleSelect: document.getElementById('sample-select'),
+    currentScenarioTitle: document.getElementById('current-scenario-title'),
+    modelCount: document.getElementById('model-count'),
+    modelSelect: document.getElementById('model-select'),
+    paramConfig: document.getElementById('param-config'),
+    systemPrompt: document.getElementById('system-prompt'),
+    userPrompt: document.getElementById('user-prompt'),
+    runBtn: document.getElementById('run-btn'),
+    resultsList: document.getElementById('results-list'),
+    statsBar: document.getElementById('stats-bar'),
+    passCount: document.getElementById('pass-count'),
+    failCount: document.getElementById('fail-count')
+};
+
+// Init
+async function init() {
+    try {
+        const scenarios = await fetchAPI('/scenarios');
+        currentState.scenarios = scenarios;
+        renderScenariosDropdown();
+
+        // Don't auto-select - let user choose
+        // Leave model dropdown empty until sample is selected
+        els.modelSelect.innerHTML = '<option value="">Select a sample first</option>';
+        els.modelSelect.disabled = true;
+    } catch (e) {
+        console.error('Failed to init:', e);
+        if (els.sampleSelect) els.sampleSelect.innerHTML = `<option>Error loading samples</option>`;
+    }
+}
+
+// Actions
+async function selectScenario(id) {
+    currentState.selectedScenarioId = id;
+    const scenario = currentState.scenarios.find(s => s.id === id);
+
+    // Update UI title
+    els.currentScenarioTitle.textContent = scenario.name;
+    els.systemPrompt.value = scenario.system_prompt;
+    els.userPrompt.value = scenario.user_prompt;
+
+    await loadModels(id);
+}
+
+async function loadModels(scenarioId) {
+    els.modelSelect.innerHTML = '<option>Loading models...</option>';
+    els.modelSelect.disabled = true;
+
+    try {
+        // Pass sample parameter to get sample-specific models
+        const models = await fetchAPI(`/models?sample=${scenarioId}`);
+
+        // Debug logging
+        console.log('Received models:', models);
+        console.log('First model:', models[0]);
+
+        currentState.models = models;
+
+        els.modelCount.textContent = `${models.length} Models`;
+
+        // Render Select with numbered display names
+        els.modelSelect.innerHTML = models.length ?
+            models.map(m => {
+                // Fallback if display_name or name is undefined
+                const displayName = m.display_name || m.name || 'Unknown Model';
+                const modelName = m.name || '';
+                console.log('Rendering model:', modelName, displayName);
+                return `<option value="${modelName}">${displayName}</option>`;
+            }).join('') :
+            '<option value="">No models found</option>';
+
+        els.modelSelect.disabled = false;
+
+        // Trigger select change to load params
+        if (models.length > 0) {
+            handleModelChange(models[0].name);
+        } else {
+            if (els.paramConfig) {
+                els.paramConfig.innerHTML = '';
+            }
+        }
+    } catch (e) {
+        console.error('Failed to load models:', e);
+        els.modelSelect.innerHTML = '<option>Error loading models</option>';
+    }
+}
+
+function handleModelChange(modelName) {
+    const model = currentState.models.find(m => m.name === modelName);
+    currentState.selectedModel = model;
+}
+
+async function runTest() {
+    if (!currentState.selectedModel) return;
+
+    els.runBtn.disabled = true;
+    els.runBtn.textContent = 'Running...';
+
+    // Clear previous results (including comprehensive test summary)
+    els.resultsList.innerHTML = '';
+
+    // Send empty config as we removed the inputs
+    const config = {};
+
+    try {
+        const result = await fetchAPI('/run', 'POST', {
+            model: currentState.selectedModel.name,
+            config: config,
+            scenario_id: currentState.selectedScenarioId,
+            user_prompt: els.userPrompt.value,
+            system_prompt: els.systemPrompt.value
+        });
+
+        addResultCard(result);
+        updateStats(result.success);
+
+    } catch (e) {
+        console.error(e);
+        addResultCard({ success: false, error: e.message, timing: 0 });
+        updateStats(false);
+    } finally {
+        els.runBtn.disabled = false;
+        els.runBtn.textContent = 'Run Test';
+    }
+}
+
+async function runComprehensiveTest() {
+    if (!currentState.selectedModel || !currentState.selectedScenarioId) return;
+
+    const comprehensiveBtn = document.getElementById('run-comprehensive-btn');
+    comprehensiveBtn.disabled = true;
+    comprehensiveBtn.textContent = 'Running comprehensive test...';
+
+    // Clear previous results
+    els.resultsList.innerHTML = '<div class="empty-state">Running comprehensive test...</div>';
+
+    try {
+        const result = await fetchAPI('/run-comprehensive', 'POST', {
+            sample: currentState.selectedScenarioId,
+            model: currentState.selectedModel.name,
+            user_prompt: els.userPrompt.value,
+            system_prompt: els.systemPrompt.value
+        });
+
+        // Clear loading message
+        els.resultsList.innerHTML = '';
+
+        // Add summary card
+        const summaryCard = document.createElement('div');
+        summaryCard.className = 'result-card summary';
+        summaryCard.innerHTML = `
+            <h4>Comprehensive Test Summary</h4>
+            <div class="summary-stats">
+                <div class="stat-item">Total Tests: <strong>${result.total_tests}</strong></div>
+                <div class="stat-item success">Passed: <strong>${result.passed}</strong></div>
+                <div class="stat-item error">Failed: <strong>${result.failed}</strong></div>
+                <div class="stat-item">Success Rate: <strong>${((result.passed / result.total_tests) * 100).toFixed(1)}%</strong></div>
+            </div>
+        `;
+        els.resultsList.appendChild(summaryCard);
+
+        // Add individual test results
+        result.results.forEach((testResult, idx) => {
+            const card = document.createElement('div');
+            card.className = `result-card ${testResult.success ? 'success' : 'error'}`;
+
+            const configStr = JSON.stringify(testResult.config);
+            const configDisplay = configStr === '{}' ? 'Default (all parameters at default)' : configStr;
+
+            card.innerHTML = `
+                <div class="result-meta">
+                    <span class="test-number">Test ${idx + 1}</span>
+                    <span class="config-label">Config: ${escapeHtml(configDisplay)}</span>
+                    <span class="timing">${testResult.timing}s</span>
+                </div>
+                <div class="result-content">
+                    ${testResult.success ? escapeHtml(testResult.response || 'No response') : escapeHtml(testResult.error || 'Unknown error')}
+                </div>
+            `;
+
+            els.resultsList.appendChild(card);
+        });
+
+        // Update global stats
+        currentState.stats.pass += result.passed;
+        currentState.stats.fail += result.failed;
+        els.passCount.textContent = currentState.stats.pass;
+        els.failCount.textContent = currentState.stats.fail;
+        els.statsBar.classList.remove('hidden');
+
+    } catch (e) {
+        console.error(e);
+        els.resultsList.innerHTML = `<div class="result-card error">
+            <div class="result-content">Error running comprehensive test: ${escapeHtml(e.message)}</div>
+        </div>`;
+    } finally {
+        comprehensiveBtn.disabled = false;
+        comprehensiveBtn.textContent = 'Run Comprehensive Test';
+    }
+}
+
+// Helpers
+async function fetchAPI(endpoint, method = 'GET', body = null) {
+    const options = {
+        method,
+        headers: {
+            'Content-Type': 'application/json'
+        }
+    };
+    if (body) options.body = JSON.stringify(body);
+
+    const res = await fetch(API_BASE + endpoint, options);
+    if (!res.ok) throw new Error(`API Error: ${res.statusText}`);
+    return await res.json();
+}
+
+function renderScenariosDropdown() {
+    const options = ['<option value="">-- Select a Sample --</option>'];
+    options.push(...currentState.scenarios.map(s =>
+        `<option value="${s.id}">${s.name}</option>`
+    ));
+    els.sampleSelect.innerHTML = options.join('');
+}
+
+function addResultCard(result) {
+    const card = document.createElement('div');
+    card.className = `result-card ${result.success ? 'success' : 'error'}`;
+
+    card.innerHTML = `
+        <div class="result-meta">
+            <span class="model-name">${currentState.selectedModel.name}</span>
+            <span class="timing">${result.timing}s</span>
+        </div>
+        <div class="result-content">${result.success ? escapeHtml(result.response) : result.error}</div>
+    `;
+
+    els.resultsList.prepend(card);
+
+    // Clear empty state
+    const empty = els.resultsList.querySelector('.empty-state');
+    if (empty) empty.remove();
+}
+
+function updateStats(success) {
+    if (success) currentState.stats.pass++;
+    else currentState.stats.fail++;
+
+    els.passCount.textContent = currentState.stats.pass;
+    els.failCount.textContent = currentState.stats.fail;
+    els.statsBar.classList.remove('hidden');
+}
+
+function escapeHtml(text) {
+    if (!text) return '';
+    return text.replace(/&/g, "&amp;")
+        .replace(/</g, "&lt;")
+        .replace(/>/g, "&gt;")
+        .replace(/"/g, "&quot;")
+        .replace(/'/g, "&#039;");
+}
+
+// Event Listeners
+els.sampleSelect.addEventListener('change', (e) => selectScenario(e.target.value));
+els.modelSelect.addEventListener('change', (e) => handleModelChange(e.target.value));
+els.runBtn.addEventListener('click', runTest);
+document.getElementById('run-comprehensive-btn').addEventListener('click', runComprehensiveTest);
+
+// Start
+init();
diff --git a/py/samples/sample-test/static/style.css b/py/samples/sample-test/static/style.css
new file mode 100644
index 0000000000..12b2451454
--- /dev/null
+++ b/py/samples/sample-test/static/style.css
@@ -0,0 +1,379 @@
+:root {
+    /* Safari-style Light Theme */
+    --bg-app: #F5F5F7;
+    /* Light gray background */
+    --bg-header: rgba(255, 255, 255, 0.72);
+    /* Glassy white */
+    --bg-card: #FFFFFF;
+    /* Pure white cards */
+    --bg-input: #E8E8ED;
+    /* Light gray inputs */
+
+    --text-primary: #1D1D1F;
+    /* Almost black */
+    --text-secondary: #86868B;
+    /* Gray text */
+
+    --accent: #0071E3;
+    /* Apple Blue */
+    --accent-hover: #0077ED;
+
+    --border: rgba(0, 0, 0, 0.1);
+    /* Subtle border */
+    --shadow-card: 0 4px 24px rgba(0, 0, 0, 0.04);
+
+    --radius-card: 18px;
+    --radius-input: 10px;
+    --radius-btn: 10px;
+
+    --success: #34C759;
+    --error: #FF3B30;
+}
+
+* {
+    box-sizing: border-box;
+    margin: 0;
+    padding: 0;
+}
+
+body {
+    font-family: -apple-system, BlinkMacSystemFont, "SF Pro Text", "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
+    background-color: var(--bg-app);
+    color: var(--text-primary);
+    line-height: 1.5;
+    height: 100vh;
+    overflow: hidden;
+    -webkit-font-smoothing: antialiased;
+}
+
+.app-container {
+    display: flex;
+    flex-direction: column;
+    height: 100vh;
+}
+
+/* Header / Top Bar */
+.top-bar {
+    height: 60px;
+    padding: 0 24px;
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    background-color: var(--bg-header);
+    backdrop-filter: blur(20px);
+    -webkit-backdrop-filter: blur(20px);
+    border-bottom: 1px solid var(--border);
+    position: sticky;
+    top: 0;
+    z-index: 100;
+}
+
+.brand {
+    display: flex;
+    align-items: center;
+    gap: 12px;
+}
+
+.logo-icon {
+    width: 28px;
+    height: 28px;
+    background: linear-gradient(135deg, var(--accent), #42a1ff);
+    border-radius: 8px;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    font-weight: 700;
+    font-size: 14px;
+    color: white;
+    box-shadow: 0 2px 8px rgba(0, 113, 227, 0.3);
+}
+
+.brand h1 {
+    font-size: 17px;
+    font-weight: 600;
+    color: var(--text-primary);
+}
+
+#current-scenario-title {
+    font-size: 15px;
+    font-weight: 500;
+    color: var(--text-secondary);
+}
+
+.badge {
+    background-color: rgba(0, 0, 0, 0.05);
+    padding: 4px 12px;
+    border-radius: 20px;
+    font-size: 12px;
+    font-weight: 500;
+    color: var(--text-secondary);
+}
+
+/* Main Layout */
+.main-content {
+    flex: 1;
+    overflow: hidden;
+    position: relative;
+}
+
+.content-grid {
+    display: grid;
+    grid-template-columns: 480px 1fr;
+    /* Fixed sidebar width */
+    gap: 24px;
+    padding: 24px;
+    height: 100%;
+    max-width: 1600px;
+    margin: 0 auto;
+}
+
+/* Panels */
+.config-panel {
+    overflow-y: auto;
+    padding-bottom: 24px;
+}
+
+.results-panel {
+    background-color: var(--bg-card);
+    border-radius: var(--radius-card);
+    box-shadow: var(--shadow-card);
+    display: flex;
+    flex-direction: column;
+    overflow: hidden;
+    height: 100%;
+    border: 1px solid var(--border);
+}
+
+/* Cards */
+.card {
+    background-color: var(--bg-card);
+    border-radius: var(--radius-card);
+    padding: 24px;
+    box-shadow: var(--shadow-card);
+    border: 1px solid var(--border);
+    margin-bottom: 24px;
+}
+
+.card h3,
+.results-header h3 {
+    font-size: 15px;
+    font-weight: 600;
+    color: var(--text-secondary);
+    text-transform: uppercase;
+    letter-spacing: 0.5px;
+    margin-bottom: 16px;
+}
+
+/* Forms */
+.form-group {
+    margin-bottom: 20px;
+}
+
+.form-group label {
+    display: block;
+    margin-bottom: 8px;
+    font-size: 13px;
+    font-weight: 500;
+    color: var(--text-primary);
+}
+
+select,
+textarea,
+input {
+    width: 100%;
+    background-color: var(--bg-input);
+    border: 1px solid transparent;
+    color: var(--text-primary);
+    padding: 10px 12px;
+    border-radius: var(--radius-input);
+    font-family: inherit;
+    font-size: 15px;
+    transition: all 0.2s ease;
+    outline: none;
+}
+
+select:hover,
+textarea:hover,
+input:hover {
+    background-color: #E0E0E5;
+}
+
+select:focus,
+textarea:focus,
+input:focus {
+    background-color: #FFFFFF;
+    border-color: var(--accent);
+    box-shadow: 0 0 0 3px rgba(0, 113, 227, 0.15);
+}
+
+textarea {
+    resize: vertical;
+    min-height: 80px;
+}
+
+/* Custom Select Arrow */
+select {
+    appearance: none;
+    -webkit-appearance: none;
+    background-image: url("data:image/svg+xml;charset=UTF-8,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24' fill='none' stroke='%2386868B' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'%3e%3cpolyline points='6 9 12 15 18 9'%3e%3c/polyline%3e%3c/svg%3e");
+    background-repeat: no-repeat;
+    background-position: right 12px center;
+    background-size: 16px;
+    padding-right: 40px;
+}
+
+/* Buttons */
+.btn-primary {
+    width: 100%;
+    background-color: var(--accent);
+    color: white;
+    border: none;
+    padding: 12px;
+    border-radius: var(--radius-btn);
+    font-size: 15px;
+    font-weight: 600;
+    cursor: pointer;
+    transition: all 0.2s ease;
+    box-shadow: 0 2px 6px rgba(0, 113, 227, 0.2);
+    margin-top: 8px;
+}
+
+.btn-primary:hover {
+    background-color: var(--accent-hover);
+    transform: scale(1.01);
+}
+
+.btn-primary:active {
+    transform: scale(0.99);
+}
+
+.btn-secondary {
+    width: 100%;
+    background-color: rgba(0, 113, 227, 0.08);
+    /* Hint of blue */
+    color: var(--accent);
+    border: none;
+    padding: 12px;
+    border-radius: var(--radius-btn);
+    font-size: 15px;
+    font-weight: 600;
+    cursor: pointer;
+    transition: all 0.2s ease;
+    margin-top: 12px;
+}
+
+.btn-secondary:hover {
+    background-color: rgba(0, 113, 227, 0.15);
+}
+
+/* Results Panel Styling */
+.results-header {
+    padding: 20px 24px;
+    border-bottom: 1px solid var(--border);
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    background-color: rgba(255, 255, 255, 0.8);
+    backdrop-filter: blur(10px);
+}
+
+.results-list {
+    flex: 1;
+    overflow-y: auto;
+    padding: 24px;
+    display: flex;
+    flex-direction: column;
+    gap: 16px;
+}
+
+/* Result Cards - Cleaner Look */
+.result-card {
+    background-color: white;
+    border-radius: 12px;
+    padding: 20px;
+    border: 1px solid var(--border);
+    box-shadow: 0 2px 8px rgba(0, 0, 0, 0.02);
+    transition: transform 0.2s;
+}
+
+.result-card:hover {
+    transform: translateY(-1px);
+    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.06);
+}
+
+.result-header {
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    margin-bottom: 12px;
+}
+
+.model-name {
+    font-weight: 600;
+    font-size: 16px;
+    color: var(--text-primary);
+}
+
+/* Status Badges */
+.status {
+    font-size: 12px;
+    font-weight: 600;
+    padding: 4px 10px;
+    border-radius: 20px;
+    text-transform: uppercase;
+    letter-spacing: 0.5px;
+}
+
+.status.success {
+    background-color: rgba(52, 199, 89, 0.1);
+    color: var(--success);
+}
+
+.status.failure {
+    background-color: rgba(255, 59, 48, 0.1);
+    color: var(--error);
+}
+
+/* Output Text */
+.output-text {
+    font-family: 'SF Mono', 'Menlo', monospace;
+    font-size: 13px;
+    background-color: #F5F5F7;
+    padding: 16px;
+    border-radius: 10px;
+    color: #424245;
+    white-space: pre-wrap;
+    border: 1px solid rgba(0, 0, 0, 0.05);
+}
+
+.error-text {
+    color: var(--error);
+    background-color: rgba(255, 59, 48, 0.05);
+}
+
+/* Empty State */
+.empty-state {
+    text-align: center;
+    color: var(--text-secondary);
+    margin-top: 60px;
+    font-size: 16px;
+}
+
+/* Scrollbars */
+::-webkit-scrollbar {
+    width: 8px;
+    height: 8px;
+}
+
+::-webkit-scrollbar-track {
+    background: transparent;
+}
+
+::-webkit-scrollbar-thumb {
+    background: #D1D1D6;
+    border-radius: 4px;
+}
+
+::-webkit-scrollbar-thumb:hover {
+    background: #8E8E93;
+}
\ No newline at end of file
diff --git a/py/samples/sample-test/test_model_performance.py b/py/samples/sample-test/test_model_performance.py
new file mode 100644
index 0000000000..9637e70817
--- /dev/null
+++ b/py/samples/sample-test/test_model_performance.py
@@ -0,0 +1,616 @@
+#!/usr/bin/env python3
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+"""Tool to test model performance with dynamic configuration variations.
+
+Usage:
+    python test_model_performance.py [--models model1,model2] [--output report.md]
+
+Example:
+    python test_model_performance.py --models googleai/gemini-2.0-flash
+"""
+
+import argparse
+import builtins
+import importlib.util
+import json
+import subprocess
+import sys
+from collections.abc import Callable
+from pathlib import Path
+from typing import Any
+
+# Mock input to prevent blocking
+builtins.input = lambda prompt="": "dummy_value"
+
+
+async def discover_models() -> dict[str, Any]:
+    """Discover all available models from Genkit registry.
+
+    Returns:
+        Dict mapping model names to model info
+    """
+    # Import Genkit
+    from genkit import Genkit
+    from genkit.plugins.google_genai import GoogleAI, VertexAI
+
+    plugins = []
+    # Initialize with GoogleAI plugin
+    try:
+        plugins.append(GoogleAI())
+    except Exception as e:
+        print(f"Warning: Failed to initialize GoogleAI plugin: {e}")
+
+    # Initialize with VertexAI plugin
+    try:
+        plugins.append(VertexAI())
+    except Exception as e:
+        # print(f"Warning: Failed to initialize VertexAI plugin: {e}")
+        pass
+
+    ai = Genkit(plugins=plugins)
+
+    registry = ai.registry
+
+    # Get all model actions via list_actions (which queries plugins)
+    from genkit.core.action import ActionKind
+    actions = await registry.list_actions(allowed_kinds=[ActionKind.MODEL])
+
+    model_info = {}
+    for meta in actions:
+        # Extract model info using metadata
+        info = meta.metadata.get('model', {})
+        model_info[meta.name] = info
+
+    return model_info
+
+
+async def discover_models_for_sample(sample_name: str) -> dict[str, Any]:
+    """Discover models used by a specific sample.
+
+    Args:
+        sample_name: Name of the sample directory (e.g., 'google-genai-hello')
+
+    Returns:
+        Dict mapping model names to model info for models used by this sample
+    """
+    from pathlib import Path
+    import importlib.util
+    import sys
+    import logging
+
+    logger = logging.getLogger(__name__)
+
+    # Find the sample directory
+    samples_dir = Path(__file__).parent.parent
+    sample_dir = samples_dir / sample_name
+
+    if not sample_dir.exists():
+        logger.warning(f"Sample directory not found: {sample_dir}")
+        return {}
+
+    # Look for main.py in common locations
+    main_file = None
+    search_paths = [
+        sample_dir / 'main.py',
+        sample_dir / 'src' / 'main.py',  # Some samples have src/ subdirectory
+        sample_dir / 'server.py',
+        sample_dir / 'app.py',
+    ]
+    
+    for candidate_path in search_paths:
+        if candidate_path.exists():
+            main_file = candidate_path
+            break
+
+    if not main_file:
+        logger.warning(f"No main file found for sample {sample_name}")
+        # Fall back to all models
+        return await discover_models()
+
+    try:
+        # Mock input() to prevent blocking on API key prompts
+        import builtins
+        import os
+        original_input = builtins.input
+        builtins.input = lambda prompt="": ""  # Return empty string for all inputs
+        
+        # Mock common API key environment variables if not set
+        env_vars_to_mock = {
+            'ANTHROPIC_API_KEY': 'mock-key',
+            'OPENAI_API_KEY': 'mock-key',
+            'GOOGLE_API_KEY': 'mock-key',
+            'GEMINI_API_KEY': 'mock-key',
+        }
+        original_env_vars = {}
+        for key, value in env_vars_to_mock.items():
+            if key not in os.environ:
+                original_env_vars[key] = None
+                os.environ[key] = value
+            else:
+                original_env_vars[key] = os.environ[key]
+        
+        try:
+            # Dynamically import the sample module
+            module_name = f"sample_{sample_name.replace('-', '_')}"
+            spec = importlib.util.spec_from_file_location(module_name, main_file)
+            if spec is None or spec.loader is None:
+                logger.warning(f"Could not load spec for {main_file}")
+                return await discover_models()
+
+            module = importlib.util.module_from_spec(spec)
+            
+            # Add to sys.modules before executing
+            old_module = sys.modules.get(module_name)
+            sys.modules[module_name] = module
+
+            try:
+                # Execute the module to initialize Genkit
+                logger.info(f"Loading sample module from {main_file}")
+                spec.loader.exec_module(module)
+
+                # Get the Genkit instance if available
+                if hasattr(module, 'ai'):
+                    ai = module.ai
+                    registry = ai.registry
+
+                    # Get all model actions
+                    from genkit.core.action import ActionKind
+                    actions = await registry.list_actions(allowed_kinds=[ActionKind.MODEL])
+
+                    model_info = {}
+                    for meta in actions:
+                        info = meta.metadata.get('model', {})
+                        model_info[meta.name] = info
+
+                    logger.info(f"Discovered {len(model_info)} models for sample {sample_name}: {list(model_info.keys())}")
+                    return model_info
+                else:
+                    logger.warning(f"Sample {sample_name} has no 'ai' attribute")
+                    
+            finally:
+                # Restore old module if it existed
+                if old_module is not None:
+                    sys.modules[module_name] = old_module
+                elif module_name in sys.modules:
+                    del sys.modules[module_name]
+                    
+        finally:
+            # Restore original input function
+            builtins.input = original_input
+            
+            # Restore original environment variables
+            for key, original_value in original_env_vars.items():
+                if original_value is None:
+                    os.environ.pop(key, None)
+                else:
+                    os.environ[key] = original_value
+
+    except ModuleNotFoundError as e:
+        error_msg = str(e)
+        logger.warning(f"Sample {sample_name} missing module: {e}")
+        
+        # Heuristic: If it's a Google sample, falling back to default/global models (Gemini) is usually safe/helpful
+        is_google_sample = 'google' in sample_name or 'gemini' in sample_name or 'vertex' in sample_name
+        
+        if is_google_sample:
+            logger.info(f"Google sample {sample_name} failed to load, falling back to default models")
+            return await discover_models()
+            
+        # For non-Google samples (e.g. Bedrock), strict failure is better than showing Gemini
+        if 'genkit.plugins.' in error_msg:
+             return {}
+             
+        # For other import errors, return empty
+        return {}
+
+    except Exception as e:
+        logger.error(f"Failed to load sample {sample_name}: {e}", exc_info=True)
+        
+        # Checking sample name again for fallback
+        if 'google' in sample_name or 'gemini' in sample_name or 'vertex' in sample_name:
+             logger.info(f"Google sample {sample_name} failed, falling back to default models")
+             return await discover_models()
+             
+        return {}  # Return empty for other failures
+
+
+
+
+
+def parse_config_schema(schema: dict[str, Any]) -> dict[str, dict[str, Any]]:
+    """Parse JSON schema to extract configuration parameters.
+
+    Args:
+        schema: JSON schema dict
+
+    Returns:
+        Dict mapping parameter names to their schema info
+    """
+    if not schema or 'properties' not in schema:
+        return {}
+
+    params = {}
+    for param_name, param_schema in schema['properties'].items():
+        # Handle 'anyOf' schemas (common in Gemini for nullable types)
+        # e.g., "maxOutputTokens": { "anyOf": [{ "type": "integer" }, { "type": "null" }] }
+        eff_schema = param_schema
+        if 'type' not in eff_schema and 'anyOf' in eff_schema:
+            for option in eff_schema['anyOf']:
+                if option.get('type') and option.get('type') != 'null':
+                    # Found the real type definition
+                    eff_schema = option
+                    break
+        
+        # If still no type, skip or look deeper (but simple type extraction is usually enough)
+        # Some fields like 'stopSequences' might be array of strings, so we need to check items too.
+        
+        param_type = eff_schema.get('type')
+        if not param_type and 'items' in eff_schema:
+             # Array type might be inferred if items is present, or check if type is 'array'
+             pass
+
+        params[param_name] = {
+            'type': param_type,
+            'minimum': eff_schema.get('minimum'),
+            'maximum': eff_schema.get('maximum'),
+            'default': param_schema.get('default'), # Default usually at top level
+            'enum': eff_schema.get('enum'),
+            'items': eff_schema.get('items'),
+        }
+
+    return params
+
+
+    return variations
+
+
+def generate_config_variations(params: dict[str, dict[str, Any]]) -> list[dict[str, Any]]:
+    """Generate configuration variations for testing.
+
+    Strategy:
+    For each discovered parameter:
+    - Numeric (temperature, top_k, top_p, etc.):
+      - Test: min, max, midpoint (if distinct from default)
+    - String (version, etc.):
+      - Test: all enum values (if enum, excluding default)
+    - Array (stop_sequences, etc.):
+      - Test: empty array, sample values (excluding default)
+    - Boolean:
+      - Test: opposite of default (or both if no default)
+
+    Args:
+        params: Parameter schema info from parse_config_schema
+
+    Returns:
+        List of config dicts to test
+    """
+    variations = []
+
+    # Test 1: Always start with all defaults (empty config)
+    variations.append({})
+
+    # Subsequent tests: Vary one parameter at a time
+    for param_name, param_info in params.items():
+        param_type = param_info['type']
+        default_value = param_info.get('default')
+
+        # Note/Optimization: We do NOT explicitly test the default value here
+        # because the first test case ({}) already covers defaults for all parameters.
+        # We only want to test deviations from the default.
+
+        if param_type == 'number' or param_type == 'integer':
+            # Numeric parameters: test min, midpoint, max individually
+            minimum = param_info.get('minimum')
+            maximum = param_info.get('maximum')
+
+            if minimum is not None and minimum != default_value:
+                variations.append({param_name: minimum})
+
+            if maximum is not None and maximum != default_value:
+                variations.append({param_name: maximum})
+
+            if minimum is not None and maximum is not None and minimum < maximum:
+                 midpoint = (minimum + maximum) / 2
+                 if param_type == 'integer':
+                     midpoint = int(midpoint)
+                 
+                 if midpoint != default_value:
+                     variations.append({param_name: midpoint})
+
+        elif param_type == 'boolean':
+            # Boolean parameters: test true, then false
+            # Deduplicate with default if present
+            if default_value is not True:
+                variations.append({param_name: True})
+            if default_value is not False:
+                variations.append({param_name: False})
+
+        elif param_type == 'string':
+            # String parameters: test each enum value individually
+            enum_values = param_info.get('enum')
+            if enum_values:
+                for value in enum_values:
+                    if value != default_value:
+                        variations.append({param_name: value})
+
+        elif param_type == 'array':
+            # Array parameters: test empty array, then sample value
+            if default_value != []:
+                variations.append({param_name: []})
+
+            # Add sample array value if items are strings
+            items_schema = param_info.get('items', {})
+            if items_schema.get('type') == 'string':
+                sample = ["STOP"]
+                if sample != default_value:
+                    variations.append({param_name: sample})
+    
+    return variations
+
+
+def run_model_test(
+    model_name: str,
+    config: dict[str, Any],
+    user_prompt: str,
+    system_prompt: str | None,
+    helper_script: Path,
+    timeout: int = 60,
+) -> dict[str, Any]:
+    """Run a single model test via subprocess.
+
+    Args:
+        model_name: Model to test
+        config: Configuration dict
+        user_prompt: User prompt
+        system_prompt: System prompt
+        helper_script: Path to run_single_model_test.py
+        timeout: Timeout in seconds
+
+    Returns:
+        Test result dict
+    """
+    cmd = [
+        "uv", "run",
+        "run_single_model_test.py",
+        model_name,
+        "--config", json.dumps(config),
+        "--user-prompt", user_prompt,
+    ]
+
+    if system_prompt:
+        cmd.extend(["--system-prompt", system_prompt])
+
+    try:
+        result_proc = subprocess.run(  # noqa: S603 - cmd constructed from trusted paths
+            cmd,
+            capture_output=True,
+            text=True,
+            timeout=timeout,
+            cwd=helper_script.parent,  # Run from script directory (samples/sample-test)
+        )
+
+        # Parse JSON output
+        stdout = result_proc.stdout
+        if "---JSON_RESULT_START---" in stdout and "---JSON_RESULT_END---" in stdout:
+            json_str = stdout.split("---JSON_RESULT_START---")[1].split("---JSON_RESULT_END---")[0].strip()
+            return json.loads(json_str)
+        else:
+            return json.loads(stdout)
+
+    except subprocess.TimeoutExpired:
+        return {
+            "success": False,
+            "response": None,
+            "error": f"Test timed out after {timeout}s",
+            "timing": timeout,
+        }
+    except Exception as e:
+        return {
+            "success": False,
+            "response": None,
+            "error": f"Subprocess failed: {e}",
+            "timing": 0.0,
+        }
+
+
+def generate_report(
+    results: list[dict[str, Any]],
+    output_file: str,
+) -> None:
+    """Generate markdown report from test results.
+
+    Args:
+        results: List of test result dicts
+        output_file: Output file path
+    """
+    total_tests = len(results)
+    passed = sum(1 for r in results if r['result']['success'])
+    failed = total_tests - passed
+    success_rate = (passed / total_tests * 100) if total_tests > 0 else 0
+
+    lines = []
+    lines.append("# Model Performance Test Report")
+    lines.append("")
+    lines.append("## Summary")
+    lines.append("")
+    lines.append(f"- **Total Tests**: {total_tests}")
+    lines.append(f"- **Passed**: {passed}")
+    lines.append(f"- **Failed**: {failed}")
+    lines.append(f"- **Success Rate**: {success_rate:.1f}%")
+    lines.append("")
+
+    # Failed tests summary
+    if failed > 0:
+        lines.append("## Failed Tests")
+        lines.append("")
+        for test in results:
+            if not test['result']['success']:
+                config_str = json.dumps(test['config'], sort_keys=True)
+                error = test['result']['error']
+                # Truncate long errors
+                if len(error) > 200:
+                    error = error[:200] + "..."
+                lines.append(f"- **{test['model']}** (config: `{config_str}`)")
+                lines.append(f"  - Error: {error}")
+                lines.append("")
+
+    # Detailed results
+    lines.append("## Detailed Results")
+    lines.append("")
+
+    # Group by model
+    models = {}
+    for test in results:
+        model_name = test['model']
+        if model_name not in models:
+            models[model_name] = []
+        models[model_name].append(test)
+
+    for model_name, model_tests in models.items():
+        lines.append(f"### {model_name}")
+        lines.append("")
+
+        for test in model_tests:
+            config_str = json.dumps(test['config'], sort_keys=True) if test['config'] else "{}"
+            status = "✅ SUCCESS" if test['result']['success'] else "❌ FAILED"
+            timing = test['result']['timing']
+
+            lines.append(f"#### Config: `{config_str}`")
+            lines.append("")
+            lines.append(f"- **Status**: {status}")
+            lines.append(f"- **Timing**: {timing}s")
+
+            if test['result']['success']:
+                response = test['result']['response']
+                # Truncate long responses
+                if len(response) > 500:
+                    response = response[:500] + "..."
+                lines.append(f"- **Response**: {response}")
+            else:
+                error = test['result']['error']
+                if len(error) > 500:
+                    error = error[:500] + "..."
+                lines.append(f"- **Error**: {error}")
+
+            lines.append("")
+
+    # Write report
+    with open(output_file, 'w') as f:
+        f.write('\n'.join(lines))
+
+
+def main() -> None:  # noqa: ASYNC240, ASYNC230 - test script, blocking I/O acceptable
+    """Test model performance with dynamic configuration variations."""
+    parser = argparse.ArgumentParser(description='Test model performance.')
+    parser.add_argument('--models', type=str, default=None, help='Comma-separated list of models to test')
+    parser.add_argument('--output', type=str, default='model_performance_report.md', help='Output report file')
+    parser.add_argument('--user-prompt', type=str, default='what is 5 +3?', help='User prompt for testing')
+    parser.add_argument('--system-prompt', type=str, default='pirate', help='System prompt for testing')
+    args = parser.parse_args()
+
+    # Suppress verbose logging
+    import logging
+    logging.basicConfig(level=logging.WARNING)
+    logging.getLogger('genkit').setLevel(logging.WARNING)
+    logging.getLogger('google').setLevel(logging.WARNING)
+
+    import asyncio
+
+    print("Discovering models...")
+    all_models = asyncio.run(discover_models())
+
+    print(f"Discovered models: {list(all_models.keys())}")
+
+    # Filter models if specified
+    if args.models:
+        model_names = [m.strip() for m in args.models.split(',')]
+        models_to_test = {k: v for k, v in all_models.items() if k in model_names}
+    else:
+        models_to_test = all_models
+
+    print(f"Found {len(models_to_test)} models to test")
+
+    if not models_to_test:
+        print("No models to test. Exiting.")
+        return
+
+    # Get helper script path
+    script_dir = Path(__file__).parent
+    helper_script = script_dir / "run_single_model_test.py"
+
+    # Run tests
+    all_results = []
+    for model_name, model_info in models_to_test.items():
+        print(f"\nTesting {model_name}...")
+
+        # Parse config schema
+        config_schema = model_info.get('customOptions', {})
+        params = parse_config_schema(config_schema)
+
+        print(f"  Found {len(params)} configurable parameters")
+
+        # Generate variations
+        variations = generate_config_variations(params)
+        print(f"  Generated {len(variations)} config variations")
+
+        # Run tests
+        for i, config in enumerate(variations, 1):
+            print(f"  Testing variation {i}/{len(variations)}...", end=' ')
+            # Flush stdout to ensure progress is visible
+            sys.stdout.flush()
+
+            result = run_model_test(
+                model_name,
+                config,
+                args.user_prompt,
+                args.system_prompt,
+                helper_script,
+            )
+
+            all_results.append({
+                'model': model_name,
+                'config': config,
+                'result': result,
+            })
+
+            status = "✅" if result['success'] else "❌"
+            print(status)
+
+    # Generate report
+    print(f"\nGenerating report: {args.output}")
+    generate_report(all_results, args.output)
+
+    # Print summary
+    total = len(all_results)
+    if total == 0:
+        print("No tests were run.")
+        return
+
+    passed = sum(1 for r in all_results if r['result']['success'])
+    failed = total - passed
+
+    print("\n" + "=" * 60)
+    print(f"Total Tests: {total}")
+    print(f"Passed: {passed}")
+    print(f"Failed: {failed}")
+    print(f"Success Rate: {(passed/total*100):.1f}%")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()
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new file mode 100644
index 0000000000..cd11a573c2
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