Cost and performance comparison
GPT-5.6 Luna vs GPT-6 Luna
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-6 Luna
- Cost / 1M Tokens
- $0.22
- 70% in · 30% out mix
- Value Index (score÷cost)
- 395.5
- Higher = better value
- Speed
- 97/100
- Context
- 1.1M
- Tier
- Fast Tier
List price from the OpenAI pricing page, verified October 12, 2026.
Check the sourceIn-depth analysis
GPT-5.6 Luna vs GPT-6 Luna: 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-6 Luna from OpenAI is a lightweight-tier model supporting 1.1M tokens in context, with standout performance in data extraction.
GPT-6 Luna is both the cheaper and the stronger model here — for the same text it costs 56% less than GPT-5.6 Luna and still leads on combined coding and reasoning by 4 points. There is no tradeoff to weigh on this pair: unless you need something specific from GPT-5.6 Luna, the cheaper model is simply the better one. GPT-5.6 Luna is priced at $0.20/M input tokens and $1.20/M output tokens. GPT-6 Luna costs $0.10/M input and $0.50/M output.
On iOPTERA's editorial scores, GPT-6 Luna leads with 86/100 for coding and 87/100 for reasoning, against GPT-5.6 Luna's 84/100 and 85/100.
Capability breakdown
Across the five core benchmark categories, here is how GPT-5.6 Luna and GPT-6 Luna stack up head to head:
Best model by task
- coding: GPT-6 Luna wins with 86/100
- reasoning: GPT-6 Luna wins with 87/100
- vision/multimodal: GPT-6 Luna wins with 86/100
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-6 Luna runs about $2.00 — GPT-6 Luna saves roughly $2.40 (55%) 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.
GPT-6 Luna and GPT-5.6 Luna were released within 2 months of each other, so they are competing on the same evaluations under roughly the same conditions. That makes a direct benchmark comparison meaningful here in a way it usually is not — neither model has the advantage of being measured on a newer, easier set of tests.
Context is effectively a tie: 1.1M against 1.1M. Neither model unlocks a document size the other cannot handle, so this axis should not enter the decision. If you were hoping context would break the tie for you, it will not.
Throughput is close enough to ignore — 98/100 versus 97/100. Neither model will feel noticeably quicker in an interactive product, so latency is not a reason to choose between them.
GPT-6 Luna wins this comparison outright — cheaper and stronger. Choose GPT-5.6 Luna only if it has a specific capability you need; on price and benchmarks it is behind on both.
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-6 Luna |
|---|---|---|
| List price (input / output) | $0.20 / $1.20 | $0.10 / $0.50 |
| Cached input | $0.0210% of the input price | $0.0110% of the input price |
| Batch API | 50% off input and output | 50% off input and output |
| Long prompts | Over 272K tokens: $0.40 / $1.80 | Over 272K tokens: $0.20 / $0.75 |
| Input with 80% cache hits | $0.056 | $0.028 |
With 80% of input served from the cache, GPT-6 Luna costs 50% less than GPT-5.6 Luna for the same input text, counting each model's tokenizer.
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-6 Luna
- $0.04
Business email
One typical email (~200 words)
- GPT-5.6 Luna
- $5.40
- GPT-6 Luna
- $2.70
Code file
50-line Python script
- GPT-5.6 Luna
- $8.00
- GPT-6 Luna
- $4.00
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-6 Luna, 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-6 Luna
$6.60/mo
$79.20/yr
Annual Savings
$100.80 saved per year
GPT-6 Luna cheaper · $8.40/mo
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