Cost and performance comparison
GPT-5.6 Luna vs GPT-5 Nano
Model AOpenAI
GPT-5.6 Luna
- Cost / 1M Tokens
- $0.50
- 70% in · 30% out mix
- Value Index (score÷cost)
- 170.0
- Higher = better value
- Speed
- 98/100
- Context
- 1.1M
- Tier
- Fast Tier
List price from the OpenAI pricing page, verified October 12, 2026.
Check the sourceModel BOpenAI
GPT-5 Nano
- Cost / 1M Tokens
- $0.16
- 70% in · 30% out mix
- Value Index (score÷cost)
- 464.5
- Higher = better value
- Speed
- 99/100
- Context
- 400K
- Tier
- Fast Tier
List price from the OpenAI pricing page, verified September 30, 2026.
Check the sourceIn-depth analysis
GPT-5.6 Luna vs GPT-5 Nano: Detailed Comparison
GPT-5.6 Luna is OpenAI's lightweight-tier language model with a 1.1M-token context window, excelling at data extraction. GPT-5 Nano from OpenAI is a lightweight-tier model supporting 400K tokens in context, with standout performance in data extraction.
GPT-5.6 Luna costs 3.2x what GPT-5 Nano does for the same text. That is a steep premium, and it buys a 25-point lead on combined coding and reasoning. Whether that trade is worth it depends entirely on how much of your traffic actually needs the harder model — for most workloads the honest answer is a small fraction of it, which is an argument for routing rather than for picking one. GPT-5.6 Luna is priced at $0.20/M input tokens and $1.20/M output tokens. GPT-5 Nano costs $0.05/M input and $0.40/M output.
On iOPTERA's editorial scores, GPT-5.6 Luna leads with 84/100 for coding and 85/100 for reasoning, against GPT-5 Nano's 72/100 and 72/100.
Capability breakdown
Across the five core benchmark categories, here is how GPT-5.6 Luna and GPT-5 Nano stack up head to head:
Best model by task
- coding: GPT-5.6 Luna wins with 84/100
- reasoning: GPT-5.6 Luna wins with 85/100
- data extraction: GPT-5.6 Luna wins with 92/100
- creative tasks: GPT-5.6 Luna wins with 84/100
- vision/multimodal: GPT-5.6 Luna wins with 85/100
Estimated monthly cost at scale
For 10M + 2M tokens of text a month (counted the way OpenAI's tokenizer counts), GPT-5.6 Luna runs about $4.40 while GPT-5 Nano runs about $1.30 — GPT-5 Nano saves roughly $3.10 (70%) every month.
What actually decides it
Both models come from OpenAI, so they share a tokenizer, an API surface, and a billing account. Switching between them is a model-string change and nothing else — no new SDK, no re-tokenizing your prompts to re-estimate cost, no second vendor to onboard. That makes routing between them far cheaper to implement than a cross-vendor split.
These are the same lab's model at the same tier, 11 months apart — so this is an upgrade question, not a choice between alternatives. GPT-5.6 Luna is the current entry; GPT-5 Nano is here because plenty of production traffic still runs on it. If you are starting something new there is little reason to pick the older one, and if you are already on it the question is whether the migration cost is worth the gain.
GPT-5.6 Luna carries the larger context window at 1.1M tokens versus 400K for GPT-5 Nano. The gap is real but not decisive — it matters if your prompts routinely run long, and is irrelevant if they sit where most production prompts sit, well under 100K. Bear in mind that filling a large window is also what makes a request expensive.
Throughput is close enough to ignore — 99/100 versus 98/100. Neither model will feel noticeably quicker in an interactive product, so latency is not a reason to choose between them.
GPT-5.6 Luna is 3.2x the price of GPT-5 Nano. Reserve it for the requests that actually need it and route the rest to GPT-5 Nano — that hybrid beats either model used alone on cost per useful answer.
What you actually pay
The list price is only the start. Prompt caching, batch processing and long prompts change the bill, and each provider sets them differently. Prices per 1M tokens.
| Pricing term | GPT-5.6 Luna | GPT-5 Nano |
|---|---|---|
| List price (input / output) | $0.20 / $1.20 | $0.05 / $0.40 |
| Cached input | $0.0210% of the input price | — |
| Batch API | 50% off input and output | — |
| Long prompts | Over 272K tokens: $0.40 / $1.80 | — |
| Input with 80% cache hits | $0.056 | — |
The last row assumes 80% of input tokens are read from the cache, as in a chat app that re-sends a long system prompt or RAG over the same documents. Cache-write and storage charges are not included.
Checked on October 8, 2026 against the pricing pages of OpenAI.
Capability scores
iOPTERA editorial scores across 5 categories — informed by public benchmarks, not measured by us
Coding
Reasoning
Extraction
Creative
Vision
Speed Score
Context Window
What Is a Token?
Models don't read words — they process tokens.
A token is roughly 4 characters of English text (~¾ of a word). Your API bill is priced per million tokens — understanding this directly reduces your costs.
Short phrase
"Hello, world!"
- GPT-5.6 Luna
- $0.08
- GPT-5 Nano
- $0.02
Business email
One typical email (~200 words)
- GPT-5.6 Luna
- $5.40
- GPT-5 Nano
- $1.35
Code file
50-line Python script
- GPT-5.6 Luna
- $8.00
- GPT-5 Nano
- $2.00
Prices shown are for 100,000 runs of each workload — one run costs a fraction of a cent on both GPT-5.6 Luna and GPT-5 Nano, so the number only becomes meaningful at production volume. Input tokens only; add your output volume in the calculator below.
How to check your token usage
response.usage.total_tokensEvery API response includes a usage object. Sum total_tokens across all calls to get your monthly figure, then use the calculator below.
Your Cost Calculator
Enter your actual monthly token usage to see real savings
Quick Presets
GPT-5.6 Luna
$15.00/mo
$180.00/yr
GPT-5 Nano
$4.65/mo
$55.80/yr
Annual Savings
$124.20 saved per year
GPT-5 Nano cheaper · $10.35/mo
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