GPT-4.1 nano API Pricing: OpenAI's Cheapest 1M-Context Model at $0.10/M Tokens

GPT-4.1 nano offers 1M context at $0.10/$0.40 per million tokens — the lowest-cost way to process long documents on OpenAI's API.

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

⚠️ Shutting Down October 23, 2026

OpenAI is retiring GPT-4.1 nano along with o3-mini and o4-mini. The designated replacement is GPT-5.6 Luna ($0.20/$1.20, 1.05M context). Plan your migration now — 77 days remaining.

TL;DR

GPT-4.1 nano Pricing Breakdown

At $0.10 per million input tokens and $0.40 per million output tokens, GPT-4.1 nano is 25x cheaper on input than GPT-5.4 ($2.50/$15) while offering a larger 1M context window. Here's how the costs scale:

Monthly Volume Input Cost Output Cost Total Cost
1M tokens$0.10$0.40$0.50
10M tokens$1.00$4.00$5.00
100M tokens$10.00$40.00$50.00
1B tokens$100.00$400.00$500.00

At 100M tokens/month, GPT-4.1 nano costs $50. The same volume on GPT-4.1 ($2/$8) would cost $700, and on GPT-5.4 ($2.50/$15) it would cost $1,275.

GPT-4.1 Family: nano vs mini vs Standard

OpenAI's GPT-4.1 family shares the same 1M context window but differs in capability and cost:

Model Input $/M Output $/M Context Best For Status
GPT-4.1 nano $0.10 $0.40 1M High-volume long-context tasks ⚠️ Retiring Oct 23
GPT-4.1 mini $0.40 $1.60 1M Balanced cost/quality, 1M context Active
GPT-4.1 $2.00 $8.00 1M Complex reasoning, highest quality Active

GPT-4.1 nano is 4x cheaper than mini and 20x cheaper than standard — the budget champion of the 1M-context family.

GPT-4.1 nano vs Other Budget Models

How does GPT-4.1 nano stack up against other cheap AI models with large context windows?

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
GPT-4.1 nano $0.10 $0.40 1M ✅ OpenAI
Gemini 2.5 Flash-Lite $0.10 $0.40 1M ✅ Google
DeepSeek V4 Flash $0.14 $0.28 1M ❌ DeepSeek
Ministral 3 3B $0.10 $0.10 128K ❌ Mistral

GPT-4.1 nano matches Gemini 2.5 Flash-Lite on price but offers vision support. Qwen 3.7 Flash is cheaper across the board, though it's from a Chinese provider which may matter for data residency requirements.

Migration Guide: What to Use After GPT-4.1 nano

With the October 23 shutdown approaching, here are your best migration options by use case:

Use Case Recommended Replacement Price Change Why
Long-document analysis GPT-5.6 Luna +100% input, +200% output Same 1M context, OpenAI's designated replacement
Cheapest 1M context Qwen 3.7 Flash -70% input, -68% output $0.03/$0.13 — cheapest 1M model from any provider
OpenAI ecosystem lock-in GPT-5 nano -50% input, same output Cheapest OpenAI model, but only 128K context
Best quality at budget price Gemini 2.5 Flash-Lite Same price $0.10/$0.40, 1M context, vision, Google infrastructure

Best Use Cases for GPT-4.1 nano

📄 Long Document Analysis

Process 500+ page contracts, legal documents, or research papers in a single API call with the 1M context window.

🔍 RAG Pipelines

Feed large chunks of retrieved context into the model for question-answering over knowledge bases.

💻 Codebase Review

Analyze entire repositories or large codebases in one pass — ideal for code review, refactoring suggestions, and documentation generation.

📊 Data Extraction

Extract structured data from long unstructured documents — invoices, reports, filings — at scale.

🌐 Multi-Language Translation

Translate long documents while maintaining context across chapters and sections.

📝 Content Summarization

Summarize books, research papers, or meeting transcripts that exceed shorter context windows.

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

Imagine you're building a document processing pipeline that handles 10,000 documents per month, averaging 50K tokens each (about 100 pages). Total: 500M tokens/month, 50/50 input/output split.

Model Monthly Cost vs GPT-4.1 nano
Qwen 3.7 Flash $40.00 20% cheaper
GPT-4.1 nano $50.00 —
Gemini 2.5 Flash-Lite $50.00 Same
DeepSeek V4 Flash $42.00 16% cheaper
GPT-4.1 mini $200.00 4x more expensive
GPT-4.1 $1,000.00 20x more expensive

Calculate Your GPT-4.1 nano Costs

Use our free calculator to estimate your monthly costs across 93 models and 11 providers.

Open Calculator → Compare Models

Frequently Asked Questions

How much does GPT-4.1 nano cost?
GPT-4.1 nano costs $0.10 per million input tokens and $0.40 per million output tokens. This makes it OpenAI's cheapest model with a 1M token context window — 25x cheaper on input than GPT-5.4 ($2.50/$15).
What is the context window of GPT-4.1 nano?
GPT-4.1 nano has a 1,048,576 (1M) token context window. This is the same as GPT-4.1, GPT-5.6 Luna, and Qwen 3.7 Flash, and 8x larger than GPT-5 nano's 128K context.
Is GPT-4.1 nano being deprecated?
Yes. GPT-4.1 nano is scheduled for shutdown on October 23, 2026. OpenAI recommends migrating to GPT-5.6 Luna ($0.20/$1.20, 1.05M context) which is the designated replacement. Luna costs 2x more on input but 3x more on output, with a slightly larger context window.
What should I migrate to from GPT-4.1 nano?
OpenAI's designated replacement is GPT-5.6 Luna ($0.20/$1.20, 1.05M). For even cheaper options: GPT-5 nano ($0.05/$0.40, 128K) has the same output price but smaller context. Qwen 3.7 Flash ($0.03/$0.13, 1M) is the cheapest 1M-context model available from any provider.
Is GPT-4.1 nano cheaper than GPT-5 nano?
No. GPT-5 nano ($0.05/$0.40) is cheaper on input (2x) and has the same output price. However, GPT-5 nano only has 128K context vs GPT-4.1 nano's 1M. For long-document tasks, GPT-4.1 nano is the better value until its Oct 23 shutdown.
What can GPT-4.1 nano be used for?
GPT-4.1 nano excels at long-context tasks that need the 1M window: document analysis, RAG pipelines, large codebase review, multi-page contract analysis, and long conversation history. For shorter tasks (classification, extraction under 128K), GPT-5 nano is cheaper.

Related Pages