Cost and performance comparison
GPT-5.6 Luna vs GPT-4o Mini
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-4o Mini
- Cost / 1M Tokens
- $0.29
- 70% in · 30% out mix
- Value Index (score÷cost)
- 273.7
- Higher = better value
- Speed
- 97/100
- Context
- 128K
- 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-4o Mini: 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-4o Mini from OpenAI is a lightweight-tier model supporting 128K tokens in context, with standout performance in data extraction.
This is a genuine tradeoff rather than a clear win. GPT-5.6 Luna leads by 17 points on combined coding and reasoning, and costs 43% more for the same text to do it. The margin is narrow enough that the answer depends on your workload: on tasks where the extra capability shows up, the premium pays for itself; on routine work it does not. GPT-5.6 Luna is priced at $0.20/M input tokens and $1.20/M output tokens. GPT-4o Mini costs $0.15/M input and $0.60/M output.
On iOPTERA's editorial scores, GPT-5.6 Luna leads with 84/100 for coding and 85/100 for reasoning, against GPT-4o Mini's 74/100 and 78/100.
Capability breakdown
Across the five core benchmark categories, here is how GPT-5.6 Luna and GPT-4o Mini 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-4o Mini wins with 95/100
- 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-4o Mini runs about $2.70 — GPT-4o Mini saves roughly $1.70 (39%) 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, 24 months apart — so this is an upgrade question, not a choice between alternatives. GPT-5.6 Luna is the current entry; GPT-4o Mini 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.
The context gap is the largest single difference on this pair: GPT-5.6 Luna takes 1.1M tokens against 128K for GPT-4o Mini, 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 — 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.
Neither model is the obvious answer. GPT-5.6 Luna leads on benchmarks, GPT-4o Mini on cost, and the gap is small on both. Run the calculator above with your real token mix — for most workloads that decides it faster than any benchmark table will.
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-4o Mini |
|---|---|---|
| List price (input / output) | $0.20 / $1.20 | $0.15 / $0.60 |
| Cached input | $0.0210% of the input price | $0.07550% 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 | — |
| Input with 80% cache hits | $0.056 | $0.09 |
With 80% of input served from the cache, GPT-5.6 Luna costs 38% less than GPT-4o Mini 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-4o Mini
- $0.06
Business email
One typical email (~200 words)
- GPT-5.6 Luna
- $5.40
- GPT-4o Mini
- $4.05
Code file
50-line Python script
- GPT-5.6 Luna
- $8.00
- GPT-4o Mini
- $6.00
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-4o Mini, 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-4o Mini
$8.55/mo
$102.60/yr
Annual Savings
$77.40 saved per year
GPT-4o Mini cheaper · $6.45/mo
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