GPT-6 Sol API Pricing: Up to 95% Off, Model ID and Coding Guide

GPT-6 Sol at a glance

Item	GPT-6 Sol
API model ID	gpt-6-sol
Positioning	Complex coding and agent-workflow tier below GPT-6 Astra
Context window	About 1.05M tokens
Maximum output	128K tokens
Knowledge cutoff	About April 20, 2026
Reasoning levels	none, low, medium, high, xhigh, max
Default reasoning	medium
Access	API, ChatGPT Work, Codex

Sol is not the GPT-6 flagship. GPT-6 Astra remains the escalation model for the hardest jobs. At the other end of the price ladder, GPT-6 Luna is the inexpensive high-volume tier. That three-way split is more useful than treating every GPT-6 request as a benchmark race.

GPT-6 Sol API pricing

All figures below are USD per 1M tokens for short-context API use.

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

For Sol, inputs above roughly 272K tokens move to long-context pricing: input is 2x and output is 1.5x. Batch and Flex are priced at half of the standard rate; Fast mode is priced at double. These multipliers matter more than the headline rate when an agent repeatedly sends very large repositories or documents.

APIMaster pricing and route availability

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

Prices and route counts were checked September 23, 2026. “From” means the lowest active route, not the only route; always use the marketplace card for the current price.

When should you use GPT-6 Sol?

Choose Sol when the task has real engineering or agentic complexity but you expect many iterations:

• implementing or repairing features across a repository;
• coding agents that need to plan, call tools, inspect results, and retry;
• structured long-context analysis where 128K output is useful;
• production loops where Astra-quality escalation is too expensive as the default.

Use Luna for classification, extraction, short transformations, and routine agent substeps. Escalate to Astra when the cost of a failed attempt outweighs the higher model bill. The right router is usually Luna first, Sol for difficult turns, and Astra for the narrow set of tasks that still fail acceptance tests.

Benchmarks and quality claims

OpenAI reports lower factual-error rates and a lower rate of coding outputs that claim completion without completing the work. It reports the latter falling from 10.4% to 1.3% in its evaluation. Those are vendor measurements, so treat them as release claims rather than a guarantee for a specific codebase.

Published and third-party figures point to a capable middle tier: OpenAI reports 33.2% on AutomationBench at xhigh; a reported DeepSWE v1.1 result at max is 68.8%. Artificial Analysis lists a GPT-6 Sol max Intelligence Index around 48, an estimated $1.06 per task, and roughly 31K output tokens per task. Benchmarks use different harnesses, prompts, and effort settings; compare them only within the same evaluation.

Early users have also described Sol as faster in wall-clock time than Astra. That is useful directionally, but it is not a portable latency SLA: queueing, tool time, output length, region, and reasoning effort all change end-to-end duration.

GPT-6 Sol vs Astra vs Luna

Need	Recommended model	Why
High-volume routine steps	gpt-6-luna	Lowest standard price; use it as the inexpensive worker tier
Complex coding and agent loops	gpt-6-sol	Stronger middle tier with 1.05M context and configurable reasoning
Highest-stakes or hardest tasks	gpt-6-astra	Flagship escalation path

For a detailed direct comparison, read GPT-6 Sol vs GPT-6 Astra. The comparison is about workload selection, not a claim that the models are interchangeable at the same reasoning setting.

Using GPT-6 Sol on APIMaster

1. Create an APIMaster account.
2. Create an API key in the console.
3. Point your OpenAI-compatible client to https://apimaster.ai/v1.
4. Set model to gpt-6-sol.
5. Start with medium reasoning and measure quality, latency, token use, and retry rate on your own workload before changing tiers.

APIMaster verifies listed routes with model fingerprint checks. Use the model marketplace card to review current availability before sending production volume.

FAQ

Is GPT-6 Sol the flagship GPT-6 model?

No. GPT-6 Sol is the tier below GPT-6 Astra. It targets complex coding and agent workflows at a lower price point; Astra is the frontier escalation tier.

What is the GPT-6 Sol API model ID?

Use gpt-6-sol.

What does GPT-6 Sol cost?

OpenAI's short-context reference price is $2 input and $10 output per 1M tokens, with $0.20 cache reads and $2.50 cache writes. Long-context, Batch/Flex, and Fast mode have different multipliers.

Is GPT-6 Sol available on APIMaster?

Yes. There are six active gpt-6-sol routes; the lowest checked route is $0.1070 / $0.5350 per 1M tokens, about 95% below OpenAI's short-context reference price. Check the live card, because route supply and pricing can change.

Should I use Sol or Luna for coding agents?

Use Luna for inexpensive routine tool loops and Sol for harder implementation, debugging, and planning turns. Evaluate the retry rate, not only the first-pass price; a cheaper model that requires repeated retries can cost more overall.

Sources and verification date

• OpenAI model and pricing documentation, checked September 23, 2026: model ID, availability, context, output limit, knowledge cutoff, reasoning settings, and pricing rules.
• Artificial Analysis, checked September 23, 2026: independent index, task-cost, and output-token estimates; results are harness-specific.
• APIMaster public marketplace data, checked September 23, 2026: active route count, prices, and fingerprint status.

Start with GPT-6 Sol

Create an APIMaster account, create a key in the console, point your client to https://apimaster.ai/v1, and call gpt-6-sol. Keep gpt-6-luna available for high-volume work and move only the difficult turns to Sol; use the live GPT-6 Sol card before you commit production traffic.