GPT-6 Sol vs GPT-6 Astra: Pricing and Up to 95% Off API Routes

What is the difference between GPT-6 Sol and GPT-6 Astra?

	GPT-6 Sol	GPT-6 Astra
API model ID	gpt-6-sol	gpt-6-astra
Position	Complex coding and agent tier	GPT-6 flagship / escalation tier
Context window	About 1.05M tokens	About 1.05M tokens
Maximum output	128K tokens	128K tokens
Best use	Repeated difficult implementation and agent work	Hardest, highest-cost-of-failure tasks
Reasoning	none through max; default medium	Use the current OpenAI model settings and pricing page

Sol is not an unreleased preview and it is not Astra with a different name. It is the model to put between a very inexpensive worker tier and the flagship, so a coding agent can spend intelligently on the turns that need more work.

Price and long-context economics

Model	Input / 1M	Cache read / 1M	Cache write / 1M	Output / 1M
GPT-6 Sol	$2.00	$0.20	$2.50	$10.00
GPT-6 Luna	$0.10	$0.01	$0.125	$0.50

Sol moves to long-context pricing above roughly 272K input tokens: input is 2x and output is 1.5x. Batch and Flex are half price, while Fast mode is double price. An agent that repeatedly sends a large repository can therefore have a bill dominated by context and cache behavior rather than by the model name alone.

APIMaster live pricing

Model	Live routes	APIMaster from	Official reference	Saving	Card
GPT-6 Sol	6	$0.1070 / $0.5350	$2.00 / $10.00	up to ~95% off	GPT-6 Sol
GPT-6 Luna	2	$0.0119 / $0.0596	$0.10 / $0.50	up to ~88% off	GPT-6 Luna

Checked September 23, 2026. Prices and route count change with supply; “from” is the lowest active route, not a promise that every channel has that price.

Which one is better for coding agents?

Use Sol as the normal strong model when an agent has to understand an unfamiliar codebase, make a multi-file change, use tools, or recover from a failed test. Its configurable reasoning lets you start at medium and increase effort only after a measured failure.

Use Astra when the task has a high cost of failure: a difficult architecture decision, a high-risk migration, a deliverable that has to be right in one attempt, or the subset of work where your own evaluation shows Sol is not meeting acceptance criteria. Astra is not the sensible default for every agent loop merely because it is the flagship.

Use Luna for classification, extraction, test triage, formatting, and other high-volume substeps. A router that starts with Luna, upgrades difficult turns to Sol, and reserves Astra for evidence-based escalation gives you a clearer cost ceiling than a one-model setup.

Capability evidence: compare like for like

OpenAI reports that Sol reduces factual errors and that its coding “false completion” rate fell from 10.4% to 1.3% in its evaluation. It also reports 33.2% on AutomationBench at xhigh. Artificial Analysis lists Sol max around 48 on its Intelligence Index, with an estimated $1.06 per task and about 31K output tokens per task.

Those numbers do not make Sol and Astra interchangeable. Different benchmarks use different prompts, tool environments, and reasoning budgets. A fair comparison fixes the repository, tools, context policy, acceptance tests, and effort level, then measures first-pass acceptance, retries, elapsed time, and total tokens.

A practical selection table

Workload	Start with	Escalate when
Extraction, classification, routine tool calls	GPT-6 Luna	Output fails simple validation
Feature work, debugging, multi-step coding	GPT-6 Sol	Tests, review, or task criteria still fail
High-stakes architecture, long autonomous runs	GPT-6 Astra	Start here when failure costs more than model spend

Use GPT-6 Sol or Astra on APIMaster

1. Create an APIMaster account.
2. Create an API key in the console.
3. Set the OpenAI-compatible base URL to https://apimaster.ai/v1.
4. Use gpt-6-sol for the strong middle tier and the current gpt-6-astra model ID for escalations.
5. Track acceptance rate, rework, cache hit rate, and total task cost before changing your routing policy.

APIMaster performs fingerprint checks for listed routes. Review the GPT-6 Sol marketplace card and GPT-6 Astra card before committing production volume.

FAQ

Is GPT-6 Sol released?

Yes. The released API model ID is gpt-6-sol.

Is GPT-6 Sol cheaper than GPT-6 Astra?

Sol is positioned below Astra and its published $2 / $10 short-context rate is designed for a lower-cost strong tier. Check OpenAI's current Astra pricing and the APIMaster market cards before comparing a particular effort level or long-context workload.

Does GPT-6 Sol have the same context window as Astra?

Both are documented around 1.05M context and 128K maximum output. The better choice still depends on task difficulty, reasoning setting, retries, and long-context pricing.

What model should I use before GPT-6 Sol?

For cheap, high-volume steps, use gpt-6-luna. For difficult coding and agent steps, use gpt-6-sol. Escalate to Astra when your evaluation shows Sol is not enough.

Sources and verification date

• OpenAI model and pricing documentation, checked September 23, 2026: released IDs, Sol specification, pricing, and reasoning options.
• Artificial Analysis, checked September 23, 2026: third-party index and cost estimates; all results are harness-specific.
• APIMaster marketplace data, checked September 23, 2026: active route count, live prices, and fingerprint status.

Start with the right GPT-6 tier

Create an APIMaster account, create a key in the console, point your client to https://apimaster.ai/v1, and set model to gpt-6-sol for complex coding and agent workflows. Keep Luna available for routine volume and escalate only the difficult work to Astra.