Claude Fable 5.2 vs GPT-6 Luna Pro
Pick up to 3 models · pricing, context and capabilities · simulate your product cost
Data updated on November 14, 2026· 230 models
Claude Fable 5.2 is Anthropic's most capable model for the most demanding technical work, with gains over Fable 5.1 in coding, reasoning, and vision.
- Reasoning estimated
- Speed estimated
- Input
- Output
- Context
- 1 M tokens
- Max output
- 128 K
- Input, $ per 1M tokens
- $8.00
- Output, $ per 1M tokens
- $40.00
- Cache read, $ per 1M
- $0.200
- Batch (input / output)
- $4.00 / $20.00
- Tool calling
- Yes
- Released
- ▲11/09/2026
- Knowledge cutoff
- 2026-06
- API id
- anthropic/claude-fable-5.2
GPT-6 Luna Pro is the same underlying model as GPT-6 Luna, served with reasoning.mode set to pro for higher-quality responses on complex tasks.
- Reasoning estimated
- Speed estimated
- ▲
- Input
- Output
- Context
- ▲1.1 M tokens
- Max output
- 128 K
- Input, $ per 1M tokens
- ▲$0.100
- Output, $ per 1M tokens
- ▲$0.500
- Cache read, $ per 1M
- $0.010
- Batch (input / output)
- $0.050 / $0.250
- Tool calling
- Yes
- Released
- 09/22/2026
- Knowledge cutoff
- —
- API id
- openai/gpt-6-luna-pro
Which is the better API choice: Claude Fable 5.2 vs GPT-6 Luna Pro?
- GPT-6 Luna Pro: cheapest input (99% less than Claude Fable 5.2)
- GPT-6 Luna Pro: cheapest output
- GPT-6 Luna Pro: largest context (1.1 M)
- Claude Fable 5.2: the newest (11/09/2026)
- GPT-6 Luna Pro: the fastest (estimated)
GPT-6 Luna Pro costs 99% less on input and 99% less on output than Claude Fable 5.2 ($0.100 / $0.500 versus $8.00 / $40.00 per million tokens). GPT-6 Luna Pro accepts more context (1.1 M). Claude Fable 5.2 and GPT-6 Luna Pro offer a batch tier at half price for jobs that do not need an immediate answer.
What would your product cost?
Estimate the monthly cost with your app's real volume. List prices, no cache or batch discounts.
With GPT-6 Luna Pro you save $276.50 a month versus Claude Fable 5.2 (99% less).
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Paste your prompt: tokens and cost per model
Rough estimate (about 4 characters per token). Nothing is sent to any server.
Cost of sending it 1,000 times (input only)
- 1GPT-6 Luna Pro OpenAI$0.008
- 2Claude Haiku 5.5 Anthropic$0.008
- 3Claude Sonnet 5.5 Anthropic$0.152
- 4Claude Sonnet 5 Anthropic$0.152
- 5Claude Opus 5.5 Anthropic$0.304
- 6Claude Opus 5 Anthropic$0.380
- 7Claude Fable 5.2 Anthropic$0.608
- 8Claude Fable 5.1 Anthropic$0.760
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See allFrequently asked questions
Which is the better API choice: Claude Fable 5.2 vs GPT-6 Luna Pro?
GPT-6 Luna Pro costs 99% less on input and 99% less on output than Claude Fable 5.2 ($0.100 / $0.500 versus $8.00 / $40.00 per million tokens). GPT-6 Luna Pro accepts more context (1.1 M). Claude Fable 5.2 and GPT-6 Luna Pro offer a batch tier at half price for jobs that do not need an immediate answer.
Which is cheaper: Claude Fable 5.2 and GPT-6 Luna Pro?
GPT-6 Luna Pro is cheaper: $0.100 per million input tokens and $0.500 per million output tokens, versus $8.00 / $40.00 for Claude Fable 5.2.
Which has more context: Claude Fable 5.2 and GPT-6 Luna Pro?
GPT-6 Luna Pro accepts 1.1 M tokens of context; Claude Fable 5.2 accepts 1 M.
Which is newer: Claude Fable 5.2 and GPT-6 Luna Pro?
Claude Fable 5.2 was released on 11/09/2026; GPT-6 Luna Pro on 09/22/2026.
What would 10,000 requests a month cost with Claude Fable 5.2 and GPT-6 Luna Pro?
With 1,500 input and 400 output tokens per request: Claude Fable 5.2: $280.00; GPT-6 Luna Pro: $3.50 a month, at list price.
Where do the prices come from and how often are they updated?
From the public catalogs of OpenRouter, models.dev and LiteLLM, which publish each provider's list prices. They sync once a day and the last update date is shown above the comparison.
What does price per million tokens mean?
It is what the provider charges per million tokens you send (input) or the model generates (output). A token is roughly 4 characters. Output almost always costs more than input.
Sources: OpenRouter, models.dev and LiteLLM. Prices in USD per million tokens, list price, no volume discounts. Prompt tokens are an estimate; each provider's tokenizer may differ.