Verified 2026 API Rates • Prompt Caching & Batch ROI

GPT-4o (Omni) vs OpenAI: GPT-6 Luna

Compare real-world API costs for GPT-4o (Omni) ($2.5/$10) vs OpenAI: GPT-6 Luna ($0.1/$0.5). Calculate Prompt Caching ROI & Batch API savings.

OpenAI: GPT-6 Luna saves up to 96% on base input tokens
OpenAI

GPT-4o (Omni)

gpt-4o
Base Input Rate
$2.50 / 1M
Output Rate
$10.00 / 1M
Prompt Cache Read
$1.25 / 1M (-50%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
-50% Off
Context Window
128k tokens
Quality Index (MMLU)
88.7
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
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 GPT-4o (Omni) and OpenAI: GPT-6 Luna:

GPT-4o (Omni) Caching Profile-50% read discount

  • Cached Read Price: $1.250 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.

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.
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
GPT-4o (Omni)$2.50 / $10.00$1.25 / $5.00 (-50%)24 Hours max (typically 30m - 2h)Bulk evaluation, dataset labeling, background summarization
OpenAI: GPT-6 Luna$0.10 / $0.50$0.05 / $0.25 (-50%)24 Hours max (typically 30m - 2h)Offline 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.

GPT-4o (Omni) Context Capacity

Provides a 128k token context window with a maximum output limit of 16.384k tokens.✓ Flat-rate billing across all prompt sizes up to max context ceiling.

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.

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.

GPT-4o (Omni):$946.88/mo
OpenAI: GPT-6 Luna:$31.38/mo
Delta Savings:-$915.50 (97%)
Architecture Verdict:OpenAI: GPT-6 Luna delivers 97% lower monthly spend ($915.50/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.

GPT-4o (Omni):$543.44/mo
OpenAI: GPT-6 Luna:$18.22/mo
Delta Savings:-$525.22 (97%)
Architecture Verdict:OpenAI: GPT-6 Luna delivers 97% lower monthly spend ($525.22/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).

GPT-4o (Omni):$1468.75/mo
OpenAI: GPT-6 Luna:$62.00/mo
Delta Savings:-$1406.75 (96%)
Architecture Verdict:OpenAI: GPT-6 Luna delivers 96% lower monthly spend ($1406.75/mo savings) for this workload profile.
ミリ秒単位の対話型シミュレータ

GPT-4o (Omni) vs OpenAI: GPT-6 Luna

エンタープライズの代表的な3大ユースケース(RAG検索、コーディングAgent、バッチ抽出)で精密試算:

Live 50ms Engine
月間リクエスト数 (Requests)100,000
入力トークン数/回 (Input Tokens)4,000
出力トークン数/回 (Output Tokens)1,000
Prompt キャッシュヒット率 (Cache Hit)70%
Batch API 分流比率0%
OpenAI: GPT-6 Luna 安価

月間推定削減額

GPT-4o (Omni)$1,650.00$16.500// 1,000リクエスト
vs
OpenAI: GPT-6 Luna$64.80$0.648// 1,000リクエスト
Developer FAQs

Frequently Asked Questions: GPT-4o (Omni) vs OpenAI: GPT-6 Luna

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

1Which model is cheaper overall: GPT-4o (Omni) or OpenAI: GPT-6 Luna?

At base pricing, GPT-4o (Omni) costs $2.5/1M input and $10/1M output, while OpenAI: GPT-6 Luna costs $0.1/1M input and $0.5/1M 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 GPT-4o (Omni) vs OpenAI: GPT-6 Luna?

GPT-4o (Omni) offers a 50% read discount ($1.25/1M), whereas OpenAI: GPT-6 Luna provides a 90% read discount ($0.01/1M). High cache hit ratios (>70%) significantly compress the cost delta in agentic and RAG architectures.

3Can I use Batch API with GPT-4o (Omni) or OpenAI: GPT-6 Luna to save 50%?

GPT-4o (Omni) supports 50% batch offload discounts for asynchronous 24-hour turnaround tasks. OpenAI: GPT-6 Luna supports 50% batch discounts.

4What are the context window limits and tiered pricing rules for GPT-4o (Omni) vs OpenAI: GPT-6 Luna?

GPT-4o (Omni) features a 128k context window with flat per-token pricing. In comparison, OpenAI: GPT-6 Luna supports 1,050k tokens with flat per-token pricing.