What is GPT-6 Astra?
Reasoning across multiple constraints
Provide the objective, source material, and acceptance criteria together. Ask Astra to compare options, identify missing evidence, and produce a recommendation with assumptions called out.
Code and document workflows
Use the API to draft code changes, review designs, organize research notes, or turn source material into a structured document. Validate factual statements and run generated code through your normal tests.
Practical use cases
Code review and implementation planning
Supply relevant files and a specific change request. Ask for a step-by-step implementation plan, risks, and test cases before requesting a patch. Avoid sending credentials or unrelated private files.
Long-document analysis
Provide reports, requirements, or meeting notes and ask for a synthesis grounded in those sources. Request references to the supplied material so important conclusions can be checked.
Technical writing
Turn product requirements into a design proposal, API guide, or release checklist. Specify the audience, format, and details that must be preserved.
Decision support
Compare options against explicit criteria such as cost, latency, maintainability, and operational requirements. Ask the model to separate known facts from estimates and unresolved questions.
Standard and long-context pricing
Up to 272,000 input tokens
Per 1M tokens: input $3, output $15, cached input $0.30, cache writes $3.75. At 100 credits per dollar, these equal 300, 1,500, 30, and 375 credits.
Above 272,000 input tokens
Per 1M tokens: input $6, output $22.50, cached input $0.60, cache writes $7.50. These equal 600, 2,250, 60, and 750 credits. The higher rates apply to the entire request, not just the tokens above the threshold.
How the threshold is counted
The input total includes uncached input plus cached reads and writes. Output tokens do not determine the context band. For example, 200,000 uncached input tokens plus 100,000 cached input tokens select the long-context band.
Estimate a request
With 100,000 uncached input tokens and 10,000 output tokens, token charges are $0.30 + $0.15 = $0.45. With 300,000 uncached input tokens and 10,000 output tokens, they are $1.80 + $0.225 = $2.025. Examples exclude cache writes and separately priced tools.
Connect GPT-6 Astra to your application
Make a first request
Send POST /api/v1/chat/completions to https://aireiter.com with Authorization: Bearer YOUR_API_KEY and Content-Type: application/json. Set model to gpt-6-astra and include a messages array with your user prompt.
Set a useful task
For a first test, ask: Review this migration plan for data-loss risks and propose verification steps. Include the actual plan, expected output format, and relevant constraints. The model cannot inspect files you have not supplied.
Validate the response
Check the HTTP status, response content, finish reason, and reported usage. A model name in the response is an API identifier; evaluate the generated content independently.
Prepare for production
Set request timeouts, keep credentials on the server, and inspect usage before scaling traffic. Retry transient failures with bounded backoff. Check partial or truncated outputs before using them.
GPT-6 Astra: pricing and API questions
/ 01What can I use GPT-6 Astra for?
Use GPT-6 Astra for coding, reasoning, drafting documents, and working through complex text-based tasks. Review generated answers before using them in production.
/ 02How much does GPT-6 Astra cost on AIReiter?
For up to 272,000 input tokens, prices per million tokens are $3 input, $15 output, $0.30 cached input, and $3.75 cache writes. These are 30% of official Standard token rates.
/ 03What changes for long-context requests?
Above 272,000 total input tokens, the entire request uses long-context rates: $6 input, $22.50 output, $0.60 cached input, and $7.50 cache writes per million tokens. Cached reads and writes count toward the input threshold.
/ 04Which model ID should I send?
Use gpt-6-astra with the AIReiter API. The internal model key is chat-gpt-6-astra. API usage requires an AIReiter API key.
/ 05What are the context and output limits?
The published model limits are a 1,050,000-token context window and up to 128,000 output tokens. Actual requests remain subject to provider and account limits.
/ 06Does every request receive a cache discount?
No. Cache read and write charges depend on the usage reported by the upstream provider. A repeated prompt does not guarantee a cache hit.