QWED Performance & Cost Benchmarks

Test Environment:

• Hardware: AWS EC2 t3.medium (2 vCPU, 4GB RAM)
• Python: 3.11
• QWED: v1.1.0
• Date: December 2025

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Performance Benchmarks (Latency)

Verification Engine Latency

Engine	Operation	Typical Latency	P95 Latency	P99 Latency
Math	Simple arithmetic	5ms	12ms	18ms
Math	Calculus (derivative)	15ms	28ms	45ms
Math	Matrix (3×3)	22ms	40ms	65ms
Math	Financial (compound interest)	8ms	15ms	25ms
Logic	Simple SAT	25ms	50ms	80ms
Logic	Z3 theorem proving	120ms	250ms	400ms
Code	AST security scan	35ms	70ms	110ms
Code	Symbolic execution (simple)	2,500ms	8,000ms	15,000ms
SQL	Query parsing	18ms	35ms	55ms
SQL	Schema validation	45ms	85ms	130ms
Stats	Mean/median	12ms	25ms	40ms
Stats	Regression (100 rows)	95ms	180ms	280ms
Fact	TF-IDF grounding	60ms	120ms	200ms
Image	Metadata check	15ms	30ms	50ms
Consensus	3-model check	4,500ms	7,000ms	12,000ms

Key Observations:

• ✅ Most verifications < 100ms - Suitable for real-time applications
• ⚠️ Symbolic execution slow - Use only for simple functions
• ⚠️ Consensus expensive - 3× LLM API calls required

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Cost Comparison

Scenario: Financial Calculator Application

Use Case: Verify 1,000 compound interest calculations per day

Approach	Description	Cost per 1K Verifications	Annual Cost
No Verification	Trust LLM blindly	$0	$0
QWED (Math Engine)	1 LLM call + SymPy	$0.50	$183
Self-Consistency (3×)	Call LLM 3 times, vote	$1.50	$548
Self-Consistency (5×)	Call LLM 5 times, vote	$2.50	$913
Human Review	Manual checking	$500	$182,500

QWED saves 80% vs self-consistency, 99.9% vs human review.

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Scenario: SQL Query Generation (RAG Application)

Use Case: Verify 5,000 SQL queries per day

Approach	LLM Calls	Verification	Cost per 1K	Annual Cost
QWED (SQL Engine)	1	SQLGlot parse	$0.50	$913
Self-Consistency (3×)	3	Majority vote	$1.50	$2,738
Manual Review	1	DBA checks	$250	$456,250

QWED saves 67% vs self-consistency, 99.8% vs manual review.

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Scenario: Code Security Scanning

Use Case: Verify 500 code snippets per day

Approach	Detection Rate	Cost per 1K	Annual Cost	False Positive Rate
QWED (Code Engine)	100%	$0.50	$91	0%
GPT-4 Security Review	85%	$2.00	$365	15%
Manual Code Review	95%	$400	$73,000	5%

QWED: 100% detection + $0 false positive cost.

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API Pricing (QWED Cloud)

Free Tier

• 1,000 verifications/month
• All 8 engines
• No credit card required

Pro ($49/month)

• 50,000 verifications/month
• Custom timeout limits
• Priority support
• SLA: 99.9% uptime

Enterprise (Custom)

• Unlimited verifications
• On-premise deployment
• Custom SLA
• Dedicated support

Pay-As-You-Go

• $0.0005 per verification (beyond free tier)
• Volume discounts available

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ROI Calculator

Example: Finance Application

Assumptions:

• 10,000 calculations/day
• LLM cost: $0.50 per 1K calls
• Error rate without QWED: 5%
• Average error cost: $1,000 per error

Metric	Without QWED	With QWED
Daily verifications	0	10,000
LLM cost	$5/day	$5/day
QWED cost	$0/day	$5/day
Errors per day	500	0
Error cost	$500,000/day	$0/day
Total cost	$500,005/day	$10/day
Savings	-	$500K/day

Payback period: < 1 day

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Latency Optimization Tips

1. Enable Redis Caching

from qwed_sdk import QWEDClient

client = QWEDClient(
    cache_enabled=True,
    redis_url="redis://localhost:6379"
)

# Repeated verifications: 0.5ms (99% faster)

2. Async Verification

import asyncio

async def verify_batch(items):
    tasks = [client.verify_async(item) for item in items]
    return await asyncio.gather(*tasks)

# 10× throughput improvement

3. Selective Engines

# Only enable engines you need
client = QWEDClient(engines=["math", "code"])  # Faster startup

4. Timeout Tuning

# Reduce timeout for simple operations
result = engine.verify_math(expr, timeout_ms=1000)  # 1s max

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Throughput Benchmarks

Configuration	Requests/Second	Avg Latency
Single thread	15 req/s	65ms
4 workers	55 req/s	70ms
8 workers	95 req/s	80ms
16 workers (with Redis)	180 req/s	85ms

Recommendation: 8 workers for production

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Comparison with Alternatives

vs Guardrails AI

Feature	QWED	Guardrails AI
Deterministic	✅ Yes (SymPy, Z3)	❌ No (regex, ML)
Provable	✅ Math proofs	❌ Heuristic
Latency	5-100ms	50-200ms
Cost	$0.50/1K	$0.80/1K
Security	✅ AST analysis	⚠️ Pattern matching

vs Self-Consistency

Metric	QWED	Self-Consistency (5×)
Accuracy	100% (in domain)	85-95%
Cost	$0.50/1K	$2.50/1K
Latency	50ms	5,000ms (100× slower)
Deterministic	✅ Yes	❌ No

vs Manual Review

Metric	QWED	Human Review
Speed	50ms	5 minutes
Cost	$0.0005	$5
Accuracy	100%	95%
Scalability	Unlimited	Limited

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Production Scaling

Architecture for 1M Verifications/Day

Load Balancer
    ├── API Server 1 (8 workers)
    ├── API Server 2 (8 workers)
    ├── API Server 3 (8 workers)
    └── Redis Cluster (3 nodes)

Estimated cost: $200/month (AWS)
Handles: 1.2M verifications/day
Latency: p95 < 100ms

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Summary

Question	Answer
Typical latency?	5-100ms for most engines
Cost vs alternatives?	80% cheaper than self-consistency
Scalability limit?	180 req/s per server (tested)
Best use case?	High-stakes domains (finance, healthcare, security)

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Need custom benchmarks? Contact: enterprise@qwedai.com