Which is more cost-effective, GPT-4.1 or GPT-6 Luna?

Based on 1M input + 1M output tokens, GPT-4.1 costs $10.00/month versus GPT-6 Luna at $0.60/month. The cheaper option depends on your token volume and prompt-to-completion ratio. Use the interactive calculator on this page to enter your exact usage.

How accurate is this cost comparison?

List prices come from each provider's own pricing page and every model page shows when they were last verified. The capability scores are iOPTERA's editorial composites — informed by public benchmarks, not benchmark results themselves; the methodology page explains how they are set.

Which model scores higher on benchmarks?

GPT-4.1 scores 89 in coding and 90 in reasoning benchmarks. GPT-6 Luna scores 86 in coding and 87 in reasoning. See the full 5-category breakdown in the Benchmark Comparison section above.

What are the context window sizes of GPT-4.1 and GPT-6 Luna?

GPT-4.1 supports a 1.0M-token context window while GPT-6 Luna supports 1.1M tokens. A larger context window lets you process more text in a single API call.

Which model is faster for real-time applications?

GPT-4.1 has a speed score of 88/100 and GPT-6 Luna scores 97/100 on our latency benchmark. For interactive chatbots and low-latency tasks, the higher speed score is preferable.

Can I calculate costs for my specific token volume?

Yes. Use the interactive cost calculator on this page. Enter your monthly token volume and adjust the prompt-to-completion ratio. You can also use presets for common scenarios like Customer Support Bots (~30M tokens/month) or Document Summarizers (~15M tokens/month).

Cost and performance comparison

GPT-4.1 vs GPT-6 Luna

Model AOpenAI

GPT-4.1

Capability score (editorial)90/100

Cost / 1M Tokens: $3.80; 70% in · 30% out mix
Value Index (score÷cost): 23.7; Higher = better value

Speed: 88/100
Context: 1.0M
Tier: Smart Tier

List price from the OpenAI pricing page, verified September 30, 2026.

Check the source

How we verify prices

Model BOpenAI

GPT-6 Luna

Capability score (editorial)87/100

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 source

How we verify prices

In-depth analysis

GPT-4.1 vs GPT-6 Luna: Detailed Comparison

GPT-4.1 is OpenAI's mid-range-tier language model with a 1.0M-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-4.1 costs 17.3x what GPT-6 Luna does for the same text. That is a steep premium, and it buys a 6-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-4.1 is priced at $2.00/M input tokens and $8.00/M output tokens. GPT-6 Luna costs $0.10/M input and $0.50/M output.

On iOPTERA's editorial scores, GPT-4.1 leads with 89/100 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-4.1 and GPT-6 Luna stack up head to head:

coding

GPT-4.1 leads

reasoning

GPT-4.1 leads

data extraction

Tie

creative tasks

GPT-4.1 leads

vision/multimodal

GPT-4.1 leads

Best model by task

coding: GPT-4.1 wins with 89/100
reasoning: GPT-4.1 wins with 90/100
creative tasks: GPT-4.1 wins with 89/100
vision/multimodal: GPT-4.1 wins with 90/100

Estimated monthly cost at scale

For 10M + 2M tokens of text a month (counted the way OpenAI's tokenizer counts), GPT-4.1 runs about $36.00 while GPT-6 Luna runs about $2.00 — GPT-6 Luna saves roughly $34.00 (94%) 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-4.1 are 17 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-4.1's scores as a floor for what it does well and be sceptical of a close-looking result.

Context is effectively a tie: 1.1M against 1.0M. 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 — 97/100 versus 88/100. Neither model will feel noticeably quicker in an interactive product, so latency is not a reason to choose between them.

GPT-4.1 is 17.3x 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 terms beyond the list price, per 1M tokens
Pricing term	GPT-4.1	GPT-6 Luna
List price (input / output)	$2.00 / $8.00	$0.10 / $0.50
Cached input	$0.5025% of the input price	$0.0110% of the input price
Batch API	50% off input and output	50% off input and output
Long prompts	No surcharge across the 1.05M window	Over 272K tokens: $0.20 / $0.75
Input with 80% cache hits	$0.80	$0.028

With 80% of input served from the cache, GPT-6 Luna costs 97% less than GPT-4.1 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

CategoryGPT-4.1GPT-6 LunaWinner

Coding

Reasoning

Extraction

Tied

Creative

Vision

GPT-4.1: 4 wins

GPT-6 Luna: 0 wins

GPT-4.1 leads overall

Speed Score

88/100vs97/100

GPT-4.1GPT-6

Context Window

1048Kvs1050K

GPT-4.1GPT-6

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!"

4 tokens

GPT-4.1: $0.80
GPT-6 Luna: $0.04

Business email

One typical email (~200 words)

~270 tokens

GPT-4.1: $54.00
GPT-6 Luna: $2.70

Code file

50-line Python script

~400 tokens

GPT-4.1: $80.00
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-4.1 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_tokens

Every 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

Monthly Token Volume

30M tokens

Prompt / Completion Split

Prompt 70%Completion 30%

GPT-4.1

$114.00/mo

$1,368.00/yr

$2.00/M input$8.00/M output

Cheaper

GPT-6 Luna

$6.60/mo

$79.20/yr

$0.10/M input$0.50/M output

Annual Savings

$1,288.80 saved per year

GPT-6 Luna cheaper · $107.40/mo

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