Choosing this model
Selection advice by Y-API. The checks below are suggested evaluations, not published test results.
Where to start
Use it for end-to-end tasks where the deliverable is the whole result — a research memo with citations, a multi-stage analysis, a design document — rather than a single transformation.
What to watch for
Flagship pricing applies, and a long-horizon task can consume far more tokens than the visible output suggests. Set a budget per task before running it at volume, and check the reasoning-token accounting.
Model specifications
These are OpenRouter model-level specifications, not a Y-API compatibility test. A particular route may accept fewer input formats, parameters or tokens. Verify the features you need with a small request; a successful text response does not validate vision or tool calling.
- Context window
- 1,050,000 tokens
- Input
- File · Image · Text
- Output
- Text
- Listed on OpenRouter
- Parameters listed by OpenRouter
include_reasoningmax_completion_tokensmax_tokensreasoningreasoning_effortresponse_formatseedstructured_outputstool_choicetoolsverbosity
API pricing & cost estimate
- Estimated credit consumed
- $35.00
- Estimated cash equivalent
- $3.50
Illustrative token budget, not measured usage or a quote. Includes input and output; excludes separate media charges, cache discounts and retries. Include billed reasoning tokens in your output budget where applicable. Actual billing follows usage returned by the service.
$1 paid adds $10 of credit. Cash equivalent = credit consumed ÷ 10; this is not the model publisher’s list price.
| Model | Estimated credit consumed | Estimated cash equivalent |
|---|---|---|
| GPT-6 Astra | $35.00 | $3.50 |
| GPT-6 Sol | $7.00 | $0.70 |
| Claude Opus 5.5 | $14.00 | $1.40 |
API integration examples
These minimal, text-only requests use the exact Y-API model ID. They do not demonstrate image, audio, video, file or tool support. The output limit also needs room for reasoning; an empty answer with finish_reason=length can mean the budget was exhausted.
A task to try
Produce a decision memo comparing two storage designs for this workload. State the assumptions, the load numbers you used, and the condition under which your recommendation flips.
Set the TOKEN environment variable to a key from your console. Run this on your server or locally; never expose a key in browser code or a public repository.
curl --fail-with-body --silent --show-error --max-time 120 \
'https://api.y-api.bestvirtualgoods.com/v1/chat/completions' \
-H "Authorization: Bearer ${TOKEN:?Set TOKEN first}" \
-H 'Content-Type: application/json' \
--data-binary @- <<'JSON'
{
"model": "openai/gpt-6-astra",
"messages": [
{
"role": "user",
"content": "Produce a decision memo comparing two storage designs for this workload. State the assumptions, the load numbers you used, and the condition under which your recommendation flips."
}
],
"max_tokens": 4096
}
JSONHow to evaluate the result
The memo should be falsifiable: named assumptions, stated numbers, and an explicit flip condition. Prose that recommends without those three is not a decision document.
Before you choose
How does Astra differ from GPT-6 Sol?
They are separate entries at different price points, with Astra positioned as the flagship. Which one you need depends on the task; run a sample of your real work through both before standardising.
Sources & scope
Technical facts come from the cited model page and, where available, its linked publisher card. A card describes that checkpoint; it is not proof of the weights a gateway serves. Prices come only from the Y-API catalog. We do not claim measured latency, uptime or benchmark scores for this endpoint.