Verified 2026 API Rates • Prompt Caching & Batch ROI

OpenAI: GPT-6 Luna vs Perplexity: Sonar

Compare real-world API costs for OpenAI: GPT-6 Luna ($0.1/$0.5) vs Perplexity: Sonar ($1/$1). Calculate Prompt Caching ROI & Batch API savings.

OpenAI: GPT-6 Luna saves up to 90% on base input tokens
OpenAI

OpenAI: GPT-6 Luna

gpt-6-luna
Base Input Rate
$0.10 / 1M
Output Rate
$0.50 / 1M
Prompt Cache Read
$0.010 / 1M (-90%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
-50% Off
Context Window
1,050k tokens
Quality Index (MMLU)
88
Perplexity

Perplexity: Sonar

sonar
Base Input Rate
$1.00 / 1M
Output Rate
$1.00 / 1M
Prompt Cache Read
$1.00 / 1M (-0%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
Not Supported
Context Window
127.072k tokens
Quality Index (MMLU)
78
Differential Module 1

Prompt Caching ROI & Write Surcharge Break-Even Analysis

Prompt caching drastically reduces input token costs for static prefixes like system prompts, tool schemas, and document chunks. Compare caching mechanisms between OpenAI: GPT-6 Luna and Perplexity: Sonar:

OpenAI: GPT-6 Luna Caching Profile-90% read discount

  • Cached Read Price: $0.010 per 1M tokens.
  • Write Surcharge: $0.00 (automatic caching with zero write penalty).
  • Minimum Cache Prefix: 1,024 tokens.
  • Amortization Rule: Immediate net savings from first cached read call.

Perplexity: Sonar Caching Profile-0% read discount

  • Cached Read Price: $1.000 per 1M tokens.
  • Write Surcharge: $0.00 (automatic caching with zero write penalty).
  • Minimum Cache Prefix: 1,024 tokens.
  • Amortization Rule: Immediate net savings from first cached read call.
Differential Module 2

Batch API 50% Discount Offload vs Real-Time SLA

Asynchronous Batch APIs cut total token expenditures in half (50% off input and output) in exchange for non-realtime execution (up to 24-hour turnaround SLA).

Model / ArchitectureStandard Input / OutputBatch 50% Off Input / OutputTurnaround SLAOptimal Use Cases
OpenAI: GPT-6 Luna$0.10 / $0.50$0.05 / $0.25 (-50%)24 Hours max (typically 30m - 2h)Bulk evaluation, dataset labeling, background summarization
Perplexity: Sonar$1.00 / $1.00Standard on-demand rateInstant real-timeOffline document translation, embedding backfills, test suites
Differential Module 3

Context Window Escalation & Tiered Pricing Architecture

Massive context windows allow ingesting entire repositories or books, but pricing models differ drastically between flat-rate vendors and tiered step-up pricing.

OpenAI: GPT-6 Luna Context Capacity

Provides a 1,050k token context window with a maximum output limit of 128k tokens.✓ Flat-rate billing across all prompt sizes up to max context ceiling.

Perplexity: Sonar Context Capacity

Provides a 127.072k token context window with a maximum output limit of 114.364k tokens.✓ Flat-rate billing across all prompt sizes up to max context ceiling.

Quill Strategic Content

Real-World Production Scenarios: Monthly Spend Projections

Pre-computed monthly engineering bill projections across 3 representative enterprise application workloads:

Scenario 1

RAG Knowledge Base & Enterprise Search

100,000 queries/month, 3,500 input tokens (system + 5 retrieved chunks), 400 output tokens, 75% prompt cache hit rate.

OpenAI: GPT-6 Luna:$31.38/mo
Perplexity: Sonar:$390.00/mo
Delta Savings:-$358.63 (92%)
Architecture Verdict:OpenAI: GPT-6 Luna delivers 92% lower monthly spend ($358.63/mo savings) for this workload profile.
Scenario 2

Multi-Turn Coding Agent & ReAct Loops

25,000 tasks/month, 8,000 input tokens (accumulating conversation context & tool schemas), 1,200 output tokens, 85% cache hit rate.

OpenAI: GPT-6 Luna:$18.22/mo
Perplexity: Sonar:$230.00/mo
Delta Savings:-$211.78 (92%)
Architecture Verdict:OpenAI: GPT-6 Luna delivers 92% lower monthly spend ($211.78/mo savings) for this workload profile.
Scenario 3

High-Throughput Offline Data Extraction

500,000 records/month, 1,500 input tokens, 250 output tokens, 100% batch offload (24-hour turnaround SLA).

OpenAI: GPT-6 Luna:$62.00/mo
Perplexity: Sonar:$875.00/mo
Delta Savings:-$813.00 (93%)
Architecture Verdict:OpenAI: GPT-6 Luna delivers 93% lower monthly spend ($813.00/mo savings) for this workload profile.
毫秒级实时交互模拟引擎

OpenAI: GPT-6 Luna 对比 Perplexity: Sonar

针对企业典型三大工程落地形态(RAG 知识库、Coding Agent 多轮、离线批量清洗)进行精确成本演算:

Live 50ms Engine
月度请求量 (Requests)100,000
单次输入 Tokens (Input)4,000
单次输出 Tokens (Output)1,000
Prompt 缓存命中率 (Cache Hit)70%
Batch API 批处理分流比例0%
OpenAI: GPT-6 Luna 更便宜

预计每月节省

OpenAI: GPT-6 Luna$64.80$0.648// 千次请求
对比
Perplexity: Sonar$500.00$5.000// 千次请求
Developer FAQs

Frequently Asked Questions: OpenAI: GPT-6 Luna vs Perplexity: Sonar

Authoritative answers on API rate limits, pricing math, break-even thresholds, and architectural migration.

1Which model is cheaper overall: OpenAI: GPT-6 Luna or Perplexity: Sonar?

At base pricing, OpenAI: GPT-6 Luna costs $0.1/1M input and $0.5/1M output, while Perplexity: Sonar costs $1/1M input and $1/1M output. The cheaper option depends on your input-to-output token ratio and whether prompt caching or batch discounts are utilized.

2How does Prompt Caching impact the cost of OpenAI: GPT-6 Luna vs Perplexity: Sonar?

OpenAI: GPT-6 Luna offers a 90% read discount ($0.01/1M), whereas Perplexity: Sonar provides a 0% read discount ($1/1M). High cache hit ratios (>70%) significantly compress the cost delta in agentic and RAG architectures.

3Can I use Batch API with OpenAI: GPT-6 Luna or Perplexity: Sonar to save 50%?

OpenAI: GPT-6 Luna supports 50% batch offload discounts for asynchronous 24-hour turnaround tasks. Perplexity: Sonar uses low base on-demand pricing.

4What are the context window limits and tiered pricing rules for OpenAI: GPT-6 Luna vs Perplexity: Sonar?

OpenAI: GPT-6 Luna features a 1,050k context window with flat per-token pricing. In comparison, Perplexity: Sonar supports 127.072k tokens with flat per-token pricing.