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GPT-6 Astra API cost

At list prices from OpenAI, GPT-6 Astra costs $10.00 per million input tokens and $50.00 per million output tokens for prompts up to 272,000 input tokens, with cached input at $1.00. Across the standard workloads below it would cost from $2,509 a month (long-form writing) to $27,983 a month (cached-prompt assistant).

It is the 13th cheapest of 13 models at 4 workloads and 12th cheapest of 12 for the cached-prompt assistant workload. Output tokens are 91% of the bill for long-form writing but 7.7% for long-document questions. Prompt caching takes the bill for the cached-prompt assistant workload from $60,833 to $27,983 a month, 54% less. Sent through the batch API, the short chat workload would cost $3,802 a month instead of $7,604.

Prices on this page last verified on Sources

Published prices

OpenAI list prices per million tokens. In our frontier tier.

GPT-6 Astra prices per million tokens
Prompt lengthInputCached inputOutputBatch inputBatch cached inputBatch output
Prompts up to 272K input tokens$10.00$1.00$50.00$5.00$0.50$25.00
Prompts over 272K input tokens$20.00$2.00$75.00$10.00$1.00$37.50

Cost at five standard workloads

The same traffic on every model, so the rank shows where GPT-6 Astra sits. “vs cheapest” compares it with the cheapest model for that workload.

GPT-6 Astra cost by workload
WorkloadRequests a dayTokens in / outPer 1,000 requestsPer monthVia batch APIRank, all modelsRank, frontier tiervs cheapest
Short chat10,0001,000 / 300$25.00$7,604$3,80213th of 133rd of 3100× (Claude Haiku 5.5)
Long-document questions1,00030,100 / 500$326.00$9,916$4,95813th of 133rd of 3100× (Claude Haiku 5.5)
Bulk tagging200,000400 / 10$4.50$27,375$13,68813th of 133rd of 3100× (Claude Haiku 5.5)
Long-form writing5001,500 / 3,000$165.00$2,509$1,25513th of 133rd of 3100× (Claude Haiku 5.5)
Cached-prompt assistant20,0008,000 / 400$46.00$27,983$13,99212th of 123rd of 3100× (Claude Haiku 5.5)

Equal costs share a rank. “Via batch API” prices the same traffic with every request sent through the provider’s batch API, using its published batch prices.

Workload assumptions

Short chat

Short questions and answers at moderate volume.

Input tokens per request
Part of the promptTokensCachedWhy
Instructions300NoShort instructions, treated as uncached.
Message and recent turns700NoChanges with every request.
Total1,000None cached
Requests a day: 10,000
A popular in-app assistant.
Output tokens per request: 300
A reply of about 220 words.
Batch API: not used
Real-time replies.

These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.

Long-document questions

Long input with a short answer: most of the cost is input tokens.

Input tokens per request
Part of the promptTokensCachedWhy
Document30,000NoAbout 22,000 words, different every time.
Question100NoOne or two sentences.
Total30,100None cached
Requests a day: 1,000
A research or legal team asking questions of whole documents.
Output tokens per request: 500
An answer of about 370 words.
Batch API: not used
Real-time answers.

These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.

Bulk tagging

Very high volume with a tiny output: a label per item.

Input tokens per request
Part of the promptTokensCachedWhy
Instructions and labels300NoShort instructions, treated as uncached.
Item100NoA short text.
Total400None cached
Requests a day: 200,000
Items such as tickets, reviews or records tagged as they arrive.
Output tokens per request: 10
One label.
Batch API: not used
Tagged as items arrive.

These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.

Long-form writing

A short brief and a long answer: most of the cost is output tokens.

Input tokens per request
Part of the promptTokensCachedWhy
Brief and style notes1,500NoDifferent for each piece.
Total1,500None cached
Requests a day: 500
Articles, reports or long emails drafted a day.
Output tokens per request: 3,000
About 2,200 words.
Batch API: not used
Drafts are wanted straight away.

These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.

Cached-prompt assistant

A large fixed prompt read from the prompt cache on every request.

Input tokens per request
Part of the promptTokensCachedWhy
Instructions and tool definitions6,000YesThe same on every request, so read from the prompt cache.
Conversation and request2,000NoChanges with every request.
Total8,00075% cached
Requests a day: 20,000
A busy assistant with long instructions and tool definitions.
Output tokens per request: 400
A reply of about 300 words.
Batch API: not used
Real-time replies.

These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.

Your traffic looks different? Enter your own figures in the calculator.

Other models in the same tier

Sources

Sources: developers.openai.com (checked )

  • Tier: Provider text: "Our most capable model for the most demanding work." Most capable in the lineup: frontier. developers.openai.com (checked )

Prices are list prices as each provider publishes them, used unchanged. How the figures are calculated: methodology.