Cost and performance comparison
GPT-6 Luna vs Claude Haiku 5.5
Model AOpenAI
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 sourceModel BAnthropic
Claude Haiku 5.5
- Cost / 1M Tokens
- $0.22
- 70% in · 30% out mix
- ≈ $0.31 for the same text, tokenizer included
- Value Index (score÷cost)
- 289.3
- Higher = better value
- Speed
- 96/100
- Context
- 1.0M
- Tier
- Fast Tier
List price from the Anthropic pricing page, verified October 12, 2026.
Its tokenizer produces about 43% more tokens than OpenAI's for the same text, so the real cost runs higher than the list price suggests. This is an estimate: the tokenizer has not been measured yet.
Check the sourceIn-depth analysis
GPT-6 Luna vs Claude Haiku 5.5: Detailed Comparison
GPT-6 Luna is OpenAI's lightweight-tier language model with a 1.1M-token context window, excelling at data extraction. Claude Haiku 5.5 from Anthropic is a lightweight-tier model supporting 1.0M tokens in context, with standout performance in data extraction.
This is a genuine tradeoff rather than a clear win. Claude Haiku 5.5 leads by 9 points on combined coding and reasoning, and costs 30% 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-6 Luna is priced at $0.10/M input tokens and $0.50/M output tokens. Claude Haiku 5.5 costs $0.10/M input and $0.50/M output.
Claude Haiku 5.5 turns the same text into about 43% more tokens than GPT-6 Luna, because their tokenizers differ — so comparing list prices per token understates what Claude Haiku 5.5 costs. For the same text, split 70% input and 30% output and counted the way OpenAI's tokenizer counts it, Claude Haiku 5.5 works out at about $0.31 per million tokens and GPT-6 Luna at $0.22. Every cost figure on this page includes that difference.
On iOPTERA's editorial scores, Claude Haiku 5.5 leads with 91/100 for coding and 91/100 for reasoning, against GPT-6 Luna's 86/100 and 87/100.
Capability breakdown
Across the five core benchmark categories, here is how GPT-6 Luna and Claude Haiku 5.5 stack up head to head:
Best model by task
- coding: Claude Haiku 5.5 wins with 91/100
- reasoning: Claude Haiku 5.5 wins with 91/100
- data extraction: Claude Haiku 5.5 wins with 93/100
- creative tasks: Claude Haiku 5.5 wins with 88/100
- vision/multimodal: Claude Haiku 5.5 wins with 89/100
Estimated monthly cost at scale
For 10M + 2M tokens of text a month (counted the way OpenAI's tokenizer counts), GPT-6 Luna runs about $2.00 while Claude Haiku 5.5 runs about $2.86 — GPT-6 Luna saves roughly $0.86 (30%) every month.
What actually decides it
GPT-6 Luna and Claude Haiku 5.5 come from different labs, which means different tokenizers, different API shapes, and a second vendor relationship. The same English text does not produce the same token count on both, so a price-per-million comparison understates the difference — measure your own prompts on each before treating the headline rates as the full story.
Claude Haiku 5.5 and GPT-6 Luna were released within 1 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 1.0M. 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 96/100. 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. Claude Haiku 5.5 leads on benchmarks, GPT-6 Luna 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-6 Luna | Claude Haiku 5.5 |
|---|---|---|
| List price (input / output) | $0.10 / $0.50 | $0.10 / $0.50 |
| Cached input | $0.0110% 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 | Over 100K tokens: $0.50 / $2.50 |
| Input with 80% cache hits | $0.028 | $0.028 |
With 80% of input served from the cache, GPT-6 Luna costs 30% less than Claude Haiku 5.5 for the same input text, counting each model's tokenizer.The tokenizer factor for Claude Haiku 5.5 is our estimate until it is measured.
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.
Claude also bills cache writes: 1.25× the input price for a 5-minute cache, 2× for one hour.
Checked on October 8, 2026 against the pricing pages of OpenAI, Anthropic.
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-6 Luna
- $0.04
- Claude Haiku 5.5
- $0.06
Business email
One typical email (~200 words)
- GPT-6 Luna
- $2.70
- Claude Haiku 5.5
- $3.86
Code file
50-line Python script
- GPT-6 Luna
- $4.00
- Claude Haiku 5.5
- $5.72
Prices shown are for 100,000 runs of each workload — one run costs a fraction of a cent on both GPT-6 Luna and Claude Haiku 5.5, 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-6 Luna
$6.60/mo
$79.20/yr
Claude Haiku 5.5
$9.44/mo
$113.26/yr
Annual Savings
$34.06 saved per year
GPT-6 Luna cheaper · $2.84/mo
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