ChatGPT API Pricing 2026: GPT-5.6, GPT-5.5, and Every Model Compared

OpenAI's ChatGPT API ranges from $0.05 to $180 per 1M tokens across 28 active models. The newest additions — GPT-5.6 Sol, Terra, and Luna — launched in July 2026 with 1.05M context windows. Meanwhile, GPT-5.4 nano ($0.20/$1.25) has become the sweet spot for most production workloads: 10x cheaper than GPT-5.5 with 400K context. Here's what every model actually costs and which one fits your budget.

Every OpenAI Model: Pricing Overview

Note: GPT-4o and GPT-4o mini are deprecated and no longer available for new API accounts. GPT-5 (Dec 11, 2026), GPT-5 mini (Dec 11), o3/o3 Pro (Dec 11), and o3-mini/o4-mini (Oct 23) have confirmed sunset dates. For new projects, use GPT-5.4 nano or GPT-5.6 Luna instead.

Which OpenAI Model Should You Use?

With 28 active models, picking the right one is overwhelming. Here's a quick decision guide:

• Cheapest option: GPT-5 nano ($0.05/$0.40) — classification, extraction, simple formatting
• Best value for production: GPT-5.4 nano ($0.20/$1.25) — chatbots, RAG, summarization with 400K context
• Best code generation: GPT-5.3 Codex ($1.75/$14) — optimized for code tasks
• Strong general-purpose: GPT-5.4 ($2.50/$15) — complex reasoning, 400K context
• Longest context (1.05M): GPT-5.6 Luna ($0.20/$1.20) — budget long-context; GPT-5.6 Sol ($4/$20) — frontier
• Maximum reasoning: GPT-5.5 Pro ($30/$180) — only for tasks that genuinely need it

Real-World Cost Scenarios

Scenario 1: Chatbot (1,000 requests/day)

Average: 800 input tokens, 300 output tokens per request. 30 days/month.

Key insight: GPT-5.4 nano at $16.20/mo is 39x cheaper than GPT-5.6 Sol for chatbot workloads. For most chatbots, the budget tier is all you need.

Scenario 2: Code Generation (200 requests/day)

Average: 3,000 input tokens, 1,200 output tokens per request. 30 days/month.

Key insight: For code generation, GPT-5.3 Codex ($648/mo) is optimized for code but costs 50% more than GPT-5.4 ($414/mo). If code quality is paramount, the Codex premium is worth it; otherwise GPT-5.4 handles most code tasks well.

Scenario 3: RAG Pipeline (500 queries/day)

Average: 5,000 input tokens (context + query), 800 output tokens per query. 30 days/month.

Scenario 4: Document Summarization (100 documents/day)

Average: 10,000 input tokens, 500 output tokens per document. 30 days/month.

The Hidden Cost: Output Token Multipliers

Output tokens are 4x to 8x more expensive than input tokens across most OpenAI models. This is where costs really add up:

What this means: Setting max_tokens is critical. An unbounded GPT-5.5 request generating 4,000 output tokens costs $0.12 in output alone — more than 100 GPT-5.4 nano requests.

OpenAI vs Competitors: Which is Cheapest?

OpenAI is rarely the cheapest option for any single use case. Its advantage is the broadest model ecosystem — 28 active models from $0.05 to $180/1M tokens — so you can mix and match by workload.

How to Calculate Your ChatGPT API Costs

Or skip the math — use the APIpulse GPT Cost Calculator to compare all OpenAI models side by side with Claude, Gemini, and DeepSeek.

5 Ways to Reduce Your OpenAI API Bill

1. Switch to GPT-5.4 nano for most tasks. At $0.20/$1.25, it handles chatbots, RAG, classification, and summarization at a fraction of GPT-5.5's cost. Most workloads don't need frontier reasoning.
2. Use GPT-5 nano for simple tasks. Classification, extraction, formatting — GPT-5 nano at $0.05/$0.40 handles these at 99% less cost than GPT-5.5.
3. Set max_tokens religiously. Output tokens cost 4-8x more than input. Setting max_tokens to 500 instead of leaving it unbounded can cut costs 60%.
4. Implement model routing. Route simple queries to GPT-5 nano, moderate to GPT-5.4 nano, and only complex reasoning to GPT-5.6 Sol. This can reduce costs 40-70%.
5. Consider GPT-oss models. GPT-oss 120B ($0.15/$0.60) and GPT-oss 20B ($0.08/$0.35) are open-source models good for batch workloads and self-hosted deployments.