perplexity-cost-tuning
Provides strategies to reduce Perplexity billing by routing queries to appropriate models, implementing caching, and monitoring token usage.
Install
mkdir -p .claude/skills/perplexity-cost-tuning && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/9044" && unzip -o skill.zip -d .claude/skills/perplexity-cost-tuning && rm skill.zipInstalls to .claude/skills/perplexity-cost-tuning
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Optimize Perplexity costs through model routing, caching, token limits,Key capabilities
- →Route queries to appropriate model tiers based on complexity
- →Limit output tokens to reduce per-request costs
- →Implement LRU caching to eliminate duplicate search fees
- →Filter search domains to reduce content processing
- →Track token usage for budget monitoring
How it works
The skill provides patterns for model routing, token limiting, and caching to minimize API costs. It uses logic to distinguish between simple factual queries and complex research tasks to select the most cost-effective model.
Inputs & outputs
When to use perplexity-cost-tuning
- →Route simple queries to cheaper sonar models
- →Implement caching to reduce redundant search fees
- →Analyze usage trends to forecast monthly bills
- →Set up budget alerts for API spend
About this skill
Perplexity Cost Tuning
Overview
Reduce Perplexity Sonar API costs. Perplexity charges per-token (input + output) plus a per-request fee that varies by search context size. The biggest cost lever is model selection: sonar-pro costs 3-15x more than sonar per request.
Pricing Reference
| Model | Input $/M tokens | Output $/M tokens | Request Fee |
|---|---|---|---|
sonar | $1 | $1 | $5 per 1K requests |
sonar-pro | $3 | $15 | $5 per 1K requests |
sonar-reasoning-pro | $3 | $15 | $5 per 1K requests |
sonar-deep-research | $2 | $8 | $5 per 1K searches |
Search context size (Low/Medium/High) affects the request fee. More context = higher fee.
Prerequisites
- Perplexity API account with usage dashboard
- Understanding of query patterns in your application
- Cache infrastructure for search results
Instructions
Step 1: Route Queries to the Right Model
// 60-70% of queries can use sonar, saving 3-15x per query
function selectModel(query: string): "sonar" | "sonar-pro" {
const simplePatterns = [
/^what is/i, /^define/i, /^who is/i, /^when did/i,
/current price/i, /^how many/i, /^is it true/i,
];
if (simplePatterns.some((p) => p.test(query))) return "sonar";
const complexPatterns = [
/compare.*vs/i, /analysis of/i, /comprehensive/i,
/pros and cons/i, /in-depth/i, /research/i,
];
if (complexPatterns.some((p) => p.test(query))) return "sonar-pro";
return "sonar"; // Default to cheapest
}
Step 2: Limit Output Tokens
set -euo pipefail
# Factual queries need ~100 tokens, not 4096
# Setting max_tokens dramatically reduces output costs
# Simple fact: 100 tokens = $0.0001 output
curl -X POST https://api.perplexity.ai/chat/completions \
-H "Authorization: Bearer $PERPLEXITY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "sonar",
"messages": [{"role": "user", "content": "Current population of Tokyo"}],
"max_tokens": 100
}'
# Research query: keep at 2048 only when needed
curl -X POST https://api.perplexity.ai/chat/completions \
-H "Authorization: Bearer $PERPLEXITY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "sonar-pro",
"messages": [{"role": "user", "content": "Compare React vs Vue in 2025 for enterprise apps"}],
"max_tokens": 2048
}'
Step 3: Cache to Eliminate Duplicate Queries
import { LRUCache } from "lru-cache";
import { createHash } from "crypto";
const searchCache = new LRUCache<string, any>({
max: 10000,
ttl: 4 * 3600_000, // 4-hour default TTL
});
async function cachedQuery(query: string, model: string) {
const key = createHash("sha256")
.update(`${model}:${query.toLowerCase().trim()}`)
.digest("hex");
const cached = searchCache.get(key);
if (cached) return cached; // $0 cost
const result = await perplexity.chat.completions.create({
model,
messages: [{ role: "user", content: query }],
});
searchCache.set(key, result);
return result;
}
// Track cache effectiveness
function cacheStats() {
return {
size: searchCache.size,
hitRate: `${((searchCache as any).hits / ((searchCache as any).hits + (searchCache as any).misses) * 100).toFixed(1)}%`,
};
}
Step 4: Use Domain Filters to Reduce Search Cost
set -euo pipefail
# Restricting search domains = less content to process = lower request fee
curl -X POST https://api.perplexity.ai/chat/completions \
-H "Authorization: Bearer $PERPLEXITY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "sonar",
"messages": [{"role": "user", "content": "Python 3.13 release notes"}],
"search_domain_filter": ["python.org", "docs.python.org"],
"max_tokens": 500
}'
Step 5: Track and Budget
class CostTracker {
private costs: Array<{ model: string; tokens: number; timestamp: Date }> = [];
record(model: string, usage: { total_tokens: number }) {
this.costs.push({
model,
tokens: usage.total_tokens,
timestamp: new Date(),
});
}
dailySummary() {
const today = this.costs.filter(
(c) => c.timestamp.toDateString() === new Date().toDateString()
);
const sonarTokens = today.filter((c) => c.model === "sonar").reduce((s, c) => s + c.tokens, 0);
const proTokens = today.filter((c) => c.model === "sonar-pro").reduce((s, c) => s + c.tokens, 0);
return {
queries: today.length,
estimatedCost: (sonarTokens * 0.000001) + (proTokens * 0.000009), // rough estimate
sonarQueries: today.filter((c) => c.model === "sonar").length,
proQueries: today.filter((c) => c.model === "sonar-pro").length,
};
}
}
Cost Optimization Checklist
- Default model is
sonar(notsonar-pro) -
max_tokensset on every request - Caching enabled for repeated queries
- Model routing by query complexity
- Domain filter used where applicable
- Monthly budget cap set on API key
- Cost tracking in production monitoring
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| High cost per query | Using sonar-pro for everything | Route simple queries to sonar |
| Low cache hit rate | Queries too unique | Normalize queries before hashing |
| Budget exhausted early | No spending caps | Set monthly budget on API key |
| Unexpectedly high bill | No max_tokens limits | Set max_tokens on all requests |
Output
- Model routing saving 60-70% on simple queries
- Token limiting reducing output costs
- Caching eliminating duplicate query costs
- Cost tracking for budget monitoring
Resources
Next Steps
For architecture patterns, see perplexity-reference-architecture.
Prerequisites
Limitations
- →Requires cache infrastructure for search results
- →Dependent on query normalization for effective caching
How it compares
This approach proactively manages costs through programmatic routing and caching rather than relying on default API settings.
Compared to similar skills
perplexity-cost-tuning side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| perplexity-cost-tuning (this skill) | 0 | 27d | Review | Intermediate |
| nextjs-developer | 328 | 2mo | No flags | Advanced |
| angular | 100 | 4mo | Review | Advanced |
| chrome-devtools | 41 | 7mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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