Cost and performance comparison
GPT-4o vs GPT-6 Luna
Model AOpenAI
GPT-4o
- Cost / 1M Tokens
- $4.75
- 70% in · 30% out mix
- Value Index (score÷cost)
- 18.9
- Higher = better value
- Speed
- 90/100
- Context
- 128K
- Tier
- Smart Tier
List price from the OpenAI pricing page, verified September 30, 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 19, 2026.
Check the sourceIn-depth analysis
GPT-4o vs GPT-6 Luna: Detailed Comparison
GPT-4o is OpenAI's mid-range-tier language model with a 128K-token context window, excelling at vision/multimodal. GPT-6 Luna from OpenAI is a lightweight-tier model supporting 1.1M tokens in context, with standout performance in data extraction.
GPT-4o costs 21.6x what GPT-6 Luna does for the same text. That is a steep premium, and it buys a 4-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-4o is priced at $2.50/M input tokens and $10.00/M output tokens. GPT-6 Luna costs $0.10/M input and $0.50/M output.
On iOPTERA's editorial scores, GPT-4o leads with 87/100 for coding and 90/100 for reasoning, against GPT-6 Luna's 86/100 and 87/100.
Capability breakdown
Across the five core benchmark categories, here is how GPT-4o and GPT-6 Luna stack up head to head:
Best model by task
- coding: GPT-4o wins with 87/100
- reasoning: GPT-4o wins with 90/100
- creative tasks: GPT-4o wins with 92/100
- vision/multimodal: GPT-4o wins with 95/100
Estimated monthly cost at scale
For 10M + 2M tokens of text a month (counted the way OpenAI's tokenizer counts), GPT-4o runs about $45.00 while GPT-6 Luna runs about $2.00 — GPT-6 Luna saves roughly $43.00 (96%) 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-4o are 28 months apart, which is more than one generation in this market. Benchmark comparisons across that gap flatter the older model: it was measured against the evaluations that existed at the time. Treat GPT-4o's scores as a floor for what it does well and be sceptical of a close-looking result.
The context gap is the largest single difference on this pair: GPT-6 Luna takes 1.1M tokens against 128K for GPT-4o, roughly 8.2x. That is the difference between feeding in a whole repository or a full contract set and having to chunk it. If your work involves documents you cannot split cleanly, this decides it on its own.
Throughput is close enough to ignore — 97/100 versus 90/100. Neither model will feel noticeably quicker in an interactive product, so latency is not a reason to choose between them.
GPT-4o is 21.6x the price of GPT-6 Luna. Reserve it for the requests that actually need it and route the rest to GPT-6 Luna — 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-4o | GPT-6 Luna |
|---|---|---|
| List price (input / output) | $2.50 / $10.00 | $0.10 / $0.50 |
| Cached input | $1.2550% 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: $0.20 / $0.75 |
| Input with 80% cache hits | $1.50 | $0.028 |
With 80% of input served from the cache, GPT-6 Luna costs 98% less than GPT-4o 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-4o
- $1.00
- GPT-6 Luna
- $0.04
Business email
One typical email (~200 words)
- GPT-4o
- $67.50
- GPT-6 Luna
- $2.70
Code file
50-line Python script
- GPT-4o
- $100.00
- 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-4o 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-4o
$142.50/mo
$1,710.00/yr
GPT-6 Luna
$6.60/mo
$79.20/yr
Annual Savings
$1,630.80 saved per year
GPT-6 Luna cheaper · $135.90/mo
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