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GPT-6 Astra

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gpt-6-astra
Model Type Astra6.1 SolSolLuna

GPT-6 Astra is the next-generation flagship OpenAI released in September 2026: a 1,050,000-token context window, up to 128,000 output tokens, reasoning_effort up to xhigh, image input, tool calling and prompt caching. Fully OpenAI-SDK compatible - set model to gpt-6-astra - and served on both /chat/completions and /responses. Pay-as-you-go, failed calls never billed; cached input bills at one tenth, and we do not add the long-context surcharge the official API applies.

ChatNext-gen flagship1.05M contextPrompt cachingImage input

What is the GPT-6 Astra API and what does it cost?

GPT-6 Astra is the flagship of OpenAI's GPT-6 family, released on September 3, 2026, with a 1,050,000-token context window and up to 128,000 output tokens. On KovAPI it costs $3.00 per 1M input tokens and $15.00 per 1M output tokens (OpenAI list price: $10 / $50 for prompts up to 272K tokens). Base URL: https://kovapi.com/v1 (OpenAI-compatible).

Measured performance

Real streaming requests sent through the public KovAPI API. Test window 2026-10-27 18:17 – 2026-10-27 18:43 UTC; sample size 100.

7.43 sTime to first token · p50
12.3 sTime to first token · p95
97%Success rate (97 of 100)
52Output tokens / second · p50
14.8 sFull response · p50 (~372 output tokens)

Failed requests in this sample: HTTP 429 × 2; stream error: The response stream did not complete. The retu × 1. Failed calls are not billed.

How this was measured
Client: a server in Los Angeles, California (US), calling https://nezhagate.com/v1 over the public internet. 100 requests to POST /v1/chat/completions with stream: true, one at a time with a 1-second gap, rotating through 10 prompts that each ask for about 200 words on a software topic, max_tokens 2500, reasoning_effort not sent (model default). Time to first token runs from sending the request to the first streamed token of any kind (answer or reasoning text). Output speed is answer tokens divided by the time from the first to the last answer token; reasoning tokens are subtracted when the API reports them, and a request is left out when the token count cannot be separated from hidden thinking. Success means HTTP 200 and a completed stream with a non-empty answer. Percentiles are nearest-rank over successful requests. The test key belongs to an internal account, so these calls are not part of the public success-rate figures elsewhere on the site. Measurements are repeated every week and this page updates itself; the date above is the latest run.

Cost example

KovAPI figures use the live price on this page; vendor figures use the vendor's published list price (sources below).

1,000 coding-assistant calls

Each call sends 20,000 input tokens (code plus instructions) and receives 2,000 output tokens, without prompt caching. Reasoning tokens count as output tokens.

WhereCostDifference
KovAPI$90.00—
OpenAI API, standard tier (prompts up to 272K tokens)$300.00KovAPI 70% cheaper

OpenAI charges 2x input and 1.5x output for the whole request once a prompt passes 272K tokens ($20 / $75 per 1M). KovAPI bills one flat rate at every prompt length, and cached input at $0.30 per 1M tokens.

Vendor list prices checked 2026-09-25: OpenAI: GPT-6 Astra model page, OpenAI API pricing.

Parameters & capabilities

"Vendor spec" is what the model's maker publishes. "Via KovAPI" is what our own requests through the gateway showed (last checked 2026-10-27).

ItemVendor specVia KovAPI
Model idgpt-6-astra OpenAI: GPT-6 Astra model page gpt-6-astra
Endpoints— /v1/chat/completions and /v1/responses
Price per 1M tokens$10 input · $1 cached input · $50 output (prompts up to 272K); $20 · $2 · $75 above 272K OpenAI: GPT-6 Astra model page $3.00 input · $0.30 cached input · $15.00 output, at any prompt length
Context window1,050,000 tokens OpenAI: GPT-6 Astra model page Not measured by us
Max output128,000 tokens OpenAI: GPT-6 Astra model page ✗ max_tokens is not enforced here (see limits below)
Streaming— ✓ Yes (SSE), with usage in the final chunk
Tool calling— ✓ Yes, OpenAI tools / tool_calls format on /v1/chat/completions
Image input (vision)— ✗ Failed in our test
JSON mode— ✓ Yes, response_format: json_object returned bare JSON
Structured output— ✓ Yes, json_schema with strict: true returned matching JSON
Reasoning effortlow, medium, high, xhigh, max OpenAI: GPT-6 Astra model page ✓ low to max accepted; omitted means medium; minimal and none are sent as low
temperature / top_p— Accepted without error but have no effect

Tool setup

Base URL https://kovapi.com/v1, your KovAPI API key, and the model id gpt-6-astra. Request and response samples (cURL, Python, Node.js) are in the GPT-6 Astra API docs.

  1. Open Cursor Settings → Models.
  2. Under API Keys, paste your KovAPI key into OpenAI API Key, turn on Override OpenAI Base URL and enter https://kovapi.com/v1.
  3. Add a custom model named gpt-6-astra, enable it, and pick it in the chat model menu.

Differences from the official API & known limits

  • max_tokens and max_completion_tokens are accepted but not enforced: in our weekly test a request with max_tokens: 60 ran to its natural length. Limit answer length in the prompt instead.
  • temperature, top_p, presence_penalty and frequency_penalty are accepted without an error but have no effect.
  • If you omit reasoning_effort on /v1/chat/completions, KovAPI sends medium (the model's own default), so a reasoning summary, when the model writes one, streams back in delta.reasoning_content; most short answers have none. minimal and none are sent as low.
  • Reasoning tokens are part of usage.completion_tokens and are billed at the output rate; usage.completion_tokens_details.reasoning_tokens shows the count when it is non-zero.
  • No long-context surcharge: the 2x input / 1.5x output multiplier OpenAI applies to prompts over 272K tokens does not exist here.
  • No Batch, Flex or priority tiers: every call is billed at the single rate shown on this page.
  • Claude Code cannot use this model (it speaks only the Anthropic Messages API, which KovAPI serves for Claude models). Use it from Cursor, Cline, n8n, Open WebUI or any OpenAI SDK.
  • If a request fails before a response starts, KovAPI retries it automatically; a stream that has already started is not retried. Failed calls are never billed.

GPT-6 Astra API: frequently asked questions

How do I call GPT-6 Astra with the OpenAI SDK?
Set the client's base URL to https://kovapi.com/v1, use your KovAPI API key, and set model to gpt-6-astra. No other code changes are needed; both /v1/chat/completions and /v1/responses work.
How much does GPT-6 Astra cost on KovAPI compared with OpenAI?
KovAPI charges $3.00 per 1M input tokens and $15.00 per 1M output tokens at any prompt length. OpenAI lists GPT-6 Astra at $10 / $50 per 1M for prompts up to 272K tokens and $20 / $75 above that.
How fast is GPT-6 Astra through KovAPI?
In our latest test (100 streaming requests, 2026-10-27), the median time to first token was 7.43 s and the 95th percentile 12.3 s, with 97% of requests succeeding. The numbers are re-measured every week.
Can I limit the answer length with max_tokens?
Not on this model: max_tokens is accepted but not enforced for GPT-6 Astra on KovAPI, so ask for a shorter answer in the prompt.
Are failed requests billed?
No. Only requests that return normally are billed, at their actual token usage. Upstream errors and timeouts cost nothing.

Live Test · Playground

Try out GPT-6 Astra right here (available after login).

Input

Advanced

The upstream for this model does not accept temperature / top_p / max_tokens (they are silently ignored). Use reasoning_effort below for thinking depth, and prompt wording for length.

Web search
Memory · multi-turn

Conversation

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About GPT-6 Astra

GPT-6 Astra is the next-generation flagship OpenAI released in September 2026, served on KovAPI through the OpenAI-compatible API: a 1,050,000-token context window, up to 128,000 output tokens, reasoning_effort for thinking depth (up to xhigh), image input, tool calling and prompt caching, on both /chat/completions and /responses. Set model to gpt-6-astra and keep your SDK and request shape. Pay-as-you-go, failed calls never billed, and cached input settles at one tenth of the input rate.

Use cases

Very long context analysis

1,050,000 tokens holds a whole repository, a contract set or a long report in one call, with no chunking and stitching of your own.

Agentic coding

It speaks the OpenAI-compatible endpoint, so Codex, Cursor and Claude Code switch to GPT-6 Astra by changing the model field alone.

Deep reasoning work

reasoning_effort goes up to xhigh, so you can spend the thinking budget on the hardest part and keep simple requests on low.

Mixed image and text input

Image input with text output: screenshot understanding, chart questions and document parsing all use the same endpoint.

How to choose

Pick GPT-6 Astra for the strongest reasoning and the hardest tasks; GPT-6 Sol is cheaper for complex coding and agentic workflows, and GPT-6 Luna fits high-volume, low-latency work. All three belong to the GPT-6 family and share a 1,050,000-token context, so switching is a one-field change.

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