GPT-5.6 Luna API Pricing: OpenAI's Cheapest 1M+ Context Model at $0.20/M

GPT-5.6 Luna offers 1.05M context at just $0.20/M input — 80% cheaper than its original price, and OpenAI's most affordable model for long-document tasks.

Updated Aug 7, 2026 · 93 models tracked across 11 providers

TL;DR

Price Drop Alert: GPT-5.6 Luna dropped from $1.00/$6.00 to $0.20/$1.20 — an 80% cut. This makes it OpenAI's cheapest model with 1M+ context, and one of the best large-context values in 2026.

GPT-5.6 Luna Pricing Breakdown

At $0.20 per million input tokens and $1.20 per million output tokens, Luna is 12.5x cheaper on input than GPT-5.4 ($2.50/M) while offering 2.6x more context. Here's how the costs scale:

Monthly Volume Input Cost Output Cost Total Cost
1M tokens$0.20$1.20$1.40
10M tokens$2.00$12.00$14.00
100M tokens$20.00$120.00$140.00
1B tokens$200.00$1,200.00$1,400.00

At 100M tokens/month, GPT-5.6 Luna costs $140. The same volume on GPT-5.6 Terra would cost $1,100, and on GPT-5.6 Sol it would cost $2,750.

GPT-5.6 Family: Sol vs Terra vs Luna

The GPT-5.6 family shares the same 1.05M context window but differs in capability and cost:

Model Input $/M Output $/M Context Best For
GPT-5.6 Luna $0.20 $1.20 1.05M Volume tasks, RAG, bulk processing
GPT-5.6 Terra $2.00 $12.00 1.05M Complex analysis, coding, agentic workflows
GPT-5.6 Sol $5.00 $30.00 1.05M Flagship reasoning, research, nuanced writing

Luna is 10x cheaper than Terra and 25x cheaper than Sol. If your task doesn't need top-tier reasoning, Luna delivers the same 1M+ context at a fraction of the cost.

How GPT-5.6 Luna Compares to Other Budget Models

Model Input $/M Output $/M Context Vision Provider
Qwen 3.7 Flash $0.03 $0.13 1M ✅ Alibaba
GPT-5 nano $0.05 $0.40 128K ❌ OpenAI
Gemini 2.5 Flash-Lite $0.10 $0.40 1M ✅ Google
DeepSeek V4 Flash $0.14 $0.28 1M ❌ DeepSeek
GPT-5.6 Luna $0.20 $1.20 1.05M ✅ OpenAI
GPT-5.4 nano $0.20 $1.25 400K ❌ OpenAI
Gemini 3.1 Flash-Lite $0.25 $1.50 1M ✅ Google

Among OpenAI models, Luna offers the best value for large-context workloads. Qwen 3.7 Flash and DeepSeek V4 Flash are cheaper per token, but Luna runs on OpenAI's infrastructure with guaranteed SLA, function calling, and structured outputs.

GPT-5.6 Luna vs GPT-5 nano: Which Budget OpenAI Model?

Both are OpenAI budget models, but they serve different use cases:

FeatureGPT-5.6 LunaGPT-5 nano
Input price$0.20/M$0.05/M
Output price$1.20/M$0.40/M
Context window1.05M128K
Vision✅❌
Model familyGPT-5.6 (newest)GPT-5 (legacy)
Best forLong docs, RAG, bulk processingSimple classification, extraction

Rule of thumb: Use GPT-5 nano for simple, high-volume tasks where context fits in 128K. Use GPT-5.6 Luna when you need 1M+ context, vision, or the improved GPT-5.6 architecture.

When to Use GPT-5.6 Luna

📄 Long-Document Analysis

Process entire codebases, legal contracts, or research papers in a single call. 1.05M context handles documents that smaller models can't fit.

🔍 RAG Pipelines

Feed large retrieval contexts directly into Luna without aggressive chunking. Cheaper per-token than Terra for retrieval-augmented generation.

📊 Bulk Data Processing

Classification, extraction, and transformation at scale. Luna's low per-token cost makes high-volume processing affordable.

🖼️ Vision Tasks

Image understanding, document OCR, and visual Q&A. Luna supports image input — unlike GPT-5 nano or GPT-5.4 nano.

💻 Codebase Understanding

Load entire repositories into context for code review, documentation generation, or migration planning. 1.05M tokens fits most projects.

🤖 Background Agents

Cost-effective backbone for agentic workflows that need large context but not flagship reasoning. Save Sol/Terra for the hard parts.

Real-World Cost: Processing 10,000 Documents/Month

Suppose you're building a document analysis pipeline that processes 10,000 documents per month, averaging 5,000 input tokens and 1,000 output tokens per document:

ModelInput CostOutput CostMonthly Total
GPT-5.6 Luna$10.00$12.00$22.00
GPT-5.6 Terra$100.00$120.00$220.00
GPT-5.4$125.00$150.00$275.00
GPT-5.6 Sol$250.00$300.00$550.00

Luna processes the same workload for $22/month — 10x cheaper than Terra and 12.5x cheaper than Sol. For bulk document tasks, the savings compound fast.

Compare 93 AI Models Side by Side

GPT-5.6 Luna is one of 93 models tracked on APIpulse. Compare pricing, context windows, and features across 11 providers.

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Frequently Asked Questions

How much does GPT-5.6 Luna cost?
GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens. This makes it OpenAI's cheapest model with a 1M+ context window — 12.5x cheaper on input than GPT-5.4 ($2.50/M).
What is the context window of GPT-5.6 Luna?
GPT-5.6 Luna has a 1.05 million token context window — the same as GPT-5.6 Sol and GPT-5.6 Terra. This is one of the largest context windows available from OpenAI, and the cheapest model to access it.
What is the difference between GPT-5.6 Luna and GPT-5.6 Terra?
GPT-5.6 Luna ($0.20/$1.20) is the budget tier of the GPT-5.6 family, while Terra ($2.00/$12.00) is the mid tier. Terra is 10x more expensive but offers stronger reasoning and instruction-following. Luna is best for high-volume tasks; Terra for complex analysis and coding.
Is GPT-5.6 Luna cheaper than GPT-5 nano?
No. GPT-5 nano ($0.05/$0.40) is cheaper per token than Luna ($0.20/$1.20). However, Luna has a 1.05M context window vs nano's 128K, and Luna is part of the newer GPT-5.6 family with improved capabilities. Choose nano for maximum cost savings; Luna when you need large context or better quality.
Was GPT-5.6 Luna's price reduced?
Yes. GPT-5.6 Luna was originally priced at $1.00/$6.00 per million tokens. It was reduced to $0.20/$1.20 — an 80% price cut. This makes it one of the best value models for large-context tasks in 2026.

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