Prompt Performance Tester

Model-agnostic prompt benchmarking across 9 providers.

Pass any model ID — provider auto-detected. Compare latency, cost, quality, and consistency across Claude, GPT, Gemini, DeepSeek, Grok, MiniMax, Qwen, Llama, and Mistral.

🚀 Why This Skill?

Problem Statement

Comparing LLM models across providers requires manual testing:

No systematic way to measure performance across models
Cost differences are significant but not easily comparable
Quality varies by use case and provider
Manual API testing is time-consuming and error-prone

The Solution

Test prompts across any model from any supported provider simultaneously. Get performance metrics and recommendations based on latency, cost, and quality.

Example Cost Comparison

For 10,000 requests/day with average 28 input + 115 output tokens:

Claude Opus 4.6: ~$30.15/day ($903/month)
Gemini 2.5 Flash-Lite: ~$0.05/day ($1.50/month)
DeepSeek Chat: ~$0.14/day ($4.20/month)
Monthly cost difference (Opus vs Flash-Lite): $901.50

✨ What You Get

Model-Agnostic Multi-Provider Testing

Pass any model ID — provider is auto-detected from the model name prefix. No hardcoded list; new models work without code changes.

| Provider | Example Models | Prefix | Required Key | |----------|---------------|--------|--------------| | Anthropic | claude-opus-4-6, claude-sonnet-4-6, claude-haiku-4-5-20251001 | claude- | ANTHROPIC_API_KEY | | OpenAI | gpt-5.2-pro, gpt-5.2, gpt-5.1 | gpt-, o1, o3 | OPENAI_API_KEY | | Google | gemini-2.5-pro, gemini-2.5-flash, gemini-2.5-flash-lite | gemini- | GOOGLE_API_KEY | | Mistral | mistral-large-latest, mistral-small-latest | mistral-, mixtral- | MISTRAL_API_KEY | | DeepSeek | deepseek-chat, deepseek-reasoner | deepseek- | DEEPSEEK_API_KEY | | xAI | grok-4-1-fast, grok-3-beta | grok- | XAI_API_KEY | | MiniMax | MiniMax-M2.1 | MiniMax, minimax | MINIMAX_API_KEY | | Qwen | qwen3.5-plus, qwen3-max-instruct | qwen | DASHSCOPE_API_KEY | | Meta Llama | meta-llama/llama-4-maverick, meta-llama/llama-3.3-70b-instruct | meta-llama/, llama- | OPENROUTER_API_KEY |

Known Pricing (per 1M tokens)

| Model | Input | Output | |-------|-------|--------| | claude-opus-4-6 | $15.00 | $75.00 | | claude-sonnet-4-6 | $3.00 | $15.00 | | claude-haiku-4-5-20251001 | $1.00 | $5.00 | | gpt-5.2-pro | $21.00 | $168.00 | | gpt-5.2 | $1.75 | $14.00 | | gpt-5.1 | $2.00 | $8.00 | | gemini-2.5-pro | $1.25 | $10.00 | | gemini-2.5-flash | $0.30 | $2.50 | | gemini-2.5-flash-lite | $0.10 | $0.40 | | mistral-large-latest | $2.00 | $6.00 | | mistral-small-latest | $0.10 | $0.30 | | deepseek-chat | $0.27 | $1.10 | | deepseek-reasoner | $0.55 | $2.19 | | grok-4-1-fast | $5.00 | $25.00 | | grok-3-beta | $3.00 | $15.00 | | MiniMax-M2.1 | $0.40 | $1.60 | | qwen3.5-plus | $0.57 | $2.29 | | qwen3-max-instruct | $1.60 | $6.40 | | meta-llama/llama-4-maverick | $0.20 | $0.60 | | meta-llama/llama-3.3-70b-instruct | $0.59 | $0.79 |

Note: Unlisted models still work — cost calculation returns $0.00 with a warning. Pricing table is for reference only, not a validation gate.

Performance Metrics

Every test measures:

⚡ Latency — Response time in milliseconds
💰 Cost — Exact API cost per request (input + output tokens)
🎯 Quality — Response quality score (0–100)
📊 Token Usage — Input and output token counts
🔄 Consistency — Variance across multiple test runs
❌ Error Tracking — API failures, timeouts, rate limits

Smart Recommendations

Get instant answers to:

Which model is fastest for your prompt?
Which is most cost-effective?
Which produces best quality responses?
How much can you save by switching providers?

📊 Real-World Example

PROMPT: "Write a professional customer service response about a delayed shipment"

┌─────────────────────────────────────────────────────────────────┐
│ GEMINI 2.5 FLASH-LITE (Google) 💰 MOST AFFORDABLE              │
├─────────────────────────────────────────────────────────────────┤
│ Latency:  523ms                                                 │
│ Cost:     $0.000025                                             │
│ Quality:  65/100                                                │
│ Tokens:   28 in / 87 out                                        │
└─────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────┐
│ DEEPSEEK CHAT (DeepSeek) 💡 BUDGET PICK                        │
├─────────────────────────────────────────────────────────────────┤
│ Latency:  710ms                                                 │
│ Cost:     $0.000048                                             │
│ Quality:  70/100                                                │
│ Tokens:   28 in / 92 out                                        │
└─────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────┐
│ CLAUDE HAIKU 4.5 (Anthropic) 🚀 BALANCED PERFORMER             │
├─────────────────────────────────────────────────────────────────┤
│ Latency:  891ms                                                 │
│ Cost:     $0.000145                                             │
│ Quality:  78/100                                                │
│ Tokens:   28 in / 102 out                                       │
└─────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────┐
│ GPT-5.2 (OpenAI) 💡 EXCELLENT QUALITY                          │
├─────────────────────────────────────────────────────────────────┤
│ Latency:  645ms                                                 │
│ Cost:     $0.000402                                             │
│ Quality:  88/100                                                │
│ Tokens:   28 in / 98 out                                        │
└─────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────┐
│ CLAUDE OPUS 4.6 (Anthropic) 🏆 HIGHEST QUALITY                 │
├─────────────────────────────────────────────────────────────────┤
│ Latency:  1,234ms                                               │
│ Cost:     $0.001875                                             │
│ Quality:  94/100                                                │
│ Tokens:   28 in / 125 out                                       │
└─────────────────────────────────────────────────────────────────┘

🎯 RECOMMENDATIONS:
1. Most cost-effective: Gemini 2.5 Flash-Lite ($0.000025/request) — 99.98% cheaper than Opus
2. Budget pick: DeepSeek Chat ($0.000048/request) — strong quality at low cost
3. Best quality: Claude Opus 4.6 (94/100) — state-of-the-art reasoning & analysis
4. Smart pick: Claude Haiku 4.5 ($0.000145/request) — 81% cheaper, 83% quality match
5. Speed + Quality: GPT-5.2 ($0.000402/request) — excellent quality at mid-range cost

💡 Potential monthly savings (10,000 requests/day, 28 input + 115 output tokens avg):
   - Using Gemini 2.5 Flash-Lite vs Opus: $903/month saved ($1.44 vs $904.50)
   - Using DeepSeek Chat vs Opus: $899/month saved ($4.50 vs $904.50)
   - Using Claude Haiku vs Opus: $731/month saved ($173.40 vs $904.50)

Use Cases

Production Deployment

Evaluate models before production selection
Compare cost vs quality tradeoffs
Benchmark API latency across providers

Prompt Development

Test prompt variations across models
Measure quality scores consistently
Compare performance metrics

Cost Analysis

Analyze LLM API spending by model
Compare provider pricing structures
Identify cost-efficient alternatives

Performance Testing

Measure latency and response times
Test consistency across multiple runs
Evaluate quality scores

🚀 Quick Start

1. Subscribe to Skill

Click "Subscribe" on ClawhHub to get access.

2. Set API Keys

Add keys for the providers you want to test:

# Anthropic (Claude models)
export ANTHROPIC_API_KEY="sk-ant-..."

# OpenAI (GPT models)
export OPENAI_API_KEY="sk-..."

# Google (Gemini models)
export GOOGLE_API_KEY="AI..."

# DeepSeek
export DEEPSEEK_API_KEY="..."

# xAI (Grok models)
export XAI_API_KEY="..."

# MiniMax
export MINIMAX_API_KEY="..."

# Alibaba (Qwen models)
export DASHSCOPE_API_KEY="..."

# OpenRouter (Meta Llama models)
export OPENROUTER_API_KEY="..."

# Mistral
export MISTRAL_API_KEY="..."

You only need keys for the providers you plan to test.

3. Install Dependencies

# Install only what you need
pip install anthropic          # Claude
pip install openai             # GPT, DeepSeek, xAI, MiniMax, Qwen, Llama
pip install google-generativeai  # Gemini
pip install mistralai          # Mistral

# Or install everything
pip install anthropic openai google-generativeai mistralai

4. Run Your First Test

Option A: Python

import os
from prompt_performance_tester import PromptPerformanceTester

tester = PromptPerformanceTester()  # reads API keys from environment

results = tester.test_prompt(
    prompt_text="Write a professional email apologizing for a delayed shipment",
    models=[
        "claude-haiku-4-5-20251001",
        "gpt-5.2",
        "gemini-2.5-flash",
        "deepseek-chat",
    ],
    num_runs=3,
    max_tokens=500
)

print(tester.format_results(results))
print(f"🏆 Best quality:  {results.best_model}")
print(f"💰 Cheapest:      {results.cheapest_model}")
print(f"⚡ Fastest:       {results.fastest_model}")

Option B: CLI

# Test across multiple models
prompt-tester test "Your prompt here" \
  --models claude-haiku-4-5-20251001 gpt-5.2 gemini-2.5-flash deepseek-chat \
  --runs 3

# Export results
prompt-tester test "Your prompt here" --export results.json

🔒 Security & Privacy

API Key Safety

Keys stored in environment variables only — never hardcoded or logged
Never transmitted to UnisAI servers
HTTPS encryption for all provider API calls

Data Privacy

Your prompts are sent only to the AI providers you select for testing
Each provider has their own data retention policy (see their privacy pages)
No data stored on UnisAI infrastructure

📚 Technical Details

System Requirements

Python: 3.9+
Dependencies: anthropic, openai, google-generativeai, mistralai (install only what you need)
Platform: macOS, Linux, Windows

Architecture

Lazy client initialization — SDK clients only loaded for providers actually tested
Prefix-based routing — PROVIDER_MAP detects provider from model name; no hardcoded whitelist
OpenAI-compat path — DeepSeek, xAI, MiniMax, Qwen, and OpenRouter all use the openai SDK with a custom base_url
Pricing table — used for cost calculation only; unknown models get cost=0 with a warning

Metrics Collected

Every test captures:

Latency: Total response time (ms)
Cost: Input + output cost based on known pricing (USD)
Quality: Heuristic response score based on length, completeness (0–100)
Tokens: Exact input/output token counts per provider
Consistency: Standard deviation across multiple runs
Errors: Timeouts, rate limits, API failures

❓ Frequently Asked Questions

Q: Do I need API keys for all 9 providers? A: No. You only need keys for the providers you want to test. If you only test Claude models, you only need ANTHROPIC_API_KEY.

Q: Who pays for the API costs? A: You do. You provide your own API keys and pay each provider directly. This skill has no per-request fees.

Q: How accurate are the cost calculations? A: Costs are calculated from the known pricing table using actual token counts. Models not in the pricing table return $0.00 — the model still runs, the cost just won't be shown.

Q: Can I test models not in the pricing table? A: Yes. Any model whose name starts with a supported prefix will run. Cost will show as $0.00 for unlisted models.

Q: Can I test prompts in non-English languages? A: Yes. All supported providers handle multiple languages.

Q: Can I use this in production/CI/CD? A: Yes. Import PromptPerformanceTester directly from Python or call via CLI.

Q: What if my prompt is very long? A: Set max_tokens appropriately. The skill passes your prompt as-is to each provider's API.

🗺️ Roadmap

✅ Current Release (v1.1.8)

Model-agnostic architecture — any model ID works via prefix detection
9 providers, 20 known models with pricing
DeepSeek, xAI Grok, MiniMax, Qwen, Meta Llama as first-class providers
Claude 4.6 series (opus-4-6, sonnet-4-6)
Lazy client initialization — only loads SDKs for providers actually used
Fixed UnisAI branding throughout

🚧 Coming Soon (v1.3)

Batch testing: Test 100+ prompts simultaneously
Historical tracking: Track model performance over time
Webhook integrations: Slack, Discord, email notifications

🔮 Future (v1.3+)

A/B testing framework: Scientific prompt experimentation
Fine-tuning insights: Which models to fine-tune for your use case
Custom benchmarks: Create your own evaluation criteria
Auto-optimization: AI-powered prompt improvement suggestions

📞 Support

Email: support@unisai.vercel.app
Website: https://unisai.vercel.app
Bug Reports: support@unisai.vercel.app

📄 License & Terms

This skill is distributed via ClawhHub under the following terms.

✅ You CAN:

Use for your own business and projects
Test prompts for internal applications
Modify source code for personal use

❌ You CANNOT:

Redistribute outside ClawhHub registry
Resell or sublicense
Use UnisAI trademark without permission

Full Terms: See LICENSE.md

📝 Changelog

[1.1.8] - 2026-02-27

Fixes & Polish

Bumped version to 1.1.8
SKILL.md fully rewritten — cleaned up formatting, removed stale content
Removed old IP watermark reference (PROPRIETARY_SKILL_VEDANT_2024) from docs
Corrected watermark to PROPRIETARY_SKILL_UNISAI_2026_MULTI_PROVIDER throughout
Fixed all UnisAI branding (was UniAI in v1.1.0 changelog)
Updated pricing table to include all 20 known models
Cleaned up FAQ, Quick Start, and Use Cases sections

[1.1.6] - 2026-02-27

🏗️ Model-Agnostic Architecture

Provider auto-detected from model name prefix — no hardcoded whitelist
Any new model works automatically without code changes
Added DeepSeek, xAI Grok, MiniMax, Qwen, Meta Llama as first-class providers (9 total)
Updated Claude to 4.6 series (claude-opus-4-6, claude-sonnet-4-6)
Lazy client initialization — only loads SDKs for providers actually tested
Unified OpenAI-compat path for DeepSeek, xAI, MiniMax, Qwen, OpenRouter

[1.1.5] - 2026-02-01

🚀 Latest Models Update

GPT-5.2 Series — Added Instant, Thinking, and Pro variants
Gemini 2.5 Series — Updated to 2.5 Pro, Flash, and Flash-Lite
Claude 4.5 pricing updates
10 total models across 3 providers

[1.1.0] - 2026-01-15

✨ Major Features

Multi-provider support — Claude, GPT, Gemini
Cross-provider cost comparison
Enhanced recommendations engine
Rebranded to UnisAI

[1.0.0] - 2024-02-02

Initial Release

Claude-only prompt testing (Haiku, Sonnet, Opus)
Performance metrics: latency, cost, quality, consistency
Basic recommendations engine

Last Updated: February 27, 2026 Current Version: 1.1.8 Status: Active & Maintained