GPT-6 Sol and Luna: What OpenAI's Cheaper Model Tiers Mean for Automation

OpenAI released updated GPT-6 Sol and Luna on September 22, 2026 at half the API cost of their GPT-5.6 predecessors, positioned below GPT-6 Astra. Here is what the three-tier lineup means for routing automation tasks by cost and complexity.

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OpenAI's GPT-6 family has three tiers. GPT-6 Astra is the flagship for the hardest reasoning and coding work, GPT-6 Sol is the mid tier for coding and agent work at a lower price, and GPT-6 Luna is the cheapest tier for high-volume tasks with a clear goal. On September 29, 2026 OpenAI followed up with GPT-6.1 Sol (gpt-6.1-sol), which its models page now lists in the Sol slot at the same price.

Updated October 23, 2026: prices, model IDs and the GPT-6.1 Sol release checked against OpenAI's API pricing page, models page and API changelog.

GPT-6 Astra vs Sol vs Luna at a glance

Prices are OpenAI's short-context API prices, read October 23, 2026 (for GPT-6.1 Sol, OpenAI's changelog sets the threshold at 272K input tokens; longer prompts are priced separately). For specs and how each model ranks against Claude and Gemini, see our pages for GPT-6 Astra, GPT-6 Sol and GPT-6 Luna, or the full LLM API pricing comparison.

The rule of thumb from the table: Luna costs a fifth of Sol, and Sol costs a fifth of Astra, on both input and output. Route each step by what it needs, not by habit.

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What OpenAI released on September 22, 2026

OpenAI released updated versions of GPT-6 Sol and GPT-6 Luna on September 22, 2026, roughly three weeks after GPT-6 Astra shipped on September 3-4, 2026. Sol and Luna are OpenAI's smaller, cheaper tiers, API pricing for both dropped 50% compared to their GPT-5.6 predecessors, and OpenAI says they were trained with methods similar to Astra's.

Astra sits at the top of the current GPT-6 lineup as the flagship model. Sol is the mid tier, built for coding and agentic work. Luna is the smallest tier, meant for high-volume, low-complexity tasks. That is the full picture of what OpenAI confirmed this week: a three-model lineup, not four. Some outlets have floated a future fourth "Terra" tier, but OpenAI has not confirmed one, so treat that as speculation, not fact.

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Why OpenAI shipped two cheaper models instead of one bigger one

OpenAI is chasing the same problem every model lab is chasing right now: token costs at scale. Sol and Luna let OpenAI sell Astra-level training methods at a fraction of Astra's price, aimed at the high-volume, repetitive work that doesn't need a flagship model. Anthropic released Claude Opus 5.5 the same day, cut about 40% for typical workloads, according to Gizmodo (September 22, 2026).

That timing was not a coincidence. Both labs are racing to make everyday, high-frequency AI usage affordable, because that's where the bulk of API spend for most companies actually lives, not in the flashy one-off flagship queries.

What Sol and Luna are actually for, according to OpenAI

According to OpenAI's own announcement, cited by TechCrunch (September 22, 2026), Sol is designed for complex tasks like coding, while Luna is built for "high-volume tasks with a clear goal, like summarizing documents, extracting information, or answering quick questions." That's a direct split between agentic, multi-step reasoning work and repetitive, single-shot classification work.

OpenAI also claims a specific factuality improvement for Sol. Per the company's internal evaluation, based on de-identified real-world conversations where users flagged mistakes, GPT-6 Sol makes about half as many mistakes as its predecessor, reaching what OpenAI calls "Astra-level reliability" at a lower cost (TechCrunch, September 22, 2026). That's OpenAI's own internal benchmark, not an independent audit, so treat it as a vendor claim until a third party replicates it.

OpenAI also published a computer-use comparison: on OSWorld 2.0 offline, GPT-6 Sol at "xhigh" effort scored 60.5% versus Claude Opus 5 at medium effort's 60.3%, at roughly 80% lower cost per task, and GPT-6 Luna at max effort reportedly beat GPT-5.6 Sol at medium effort at about one-tenth the cost (9to5Mac, September 22, 2026, citing OpenAI's announcement). Again, this is OpenAI's own benchmark, run on OpenAI's chosen settings, not a neutral third-party test.

Availability: who gets access and when

Sol and Luna are rolling out to ChatGPT Work and Codex for Plus, Pro, Business, Enterprise, and Edu accounts, plus the API, starting September 22, 2026 (9to5Mac, TechCrunch). Free and Go users get access to Luna through the desktop app. Enterprise workspace admins need to enable the new models manually before their teams see them.

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What a tiered model lineup means for how you should route automation work

A three-tier lineup (flagship, mid, small) is a routing decision waiting to happen, not just a pricing update. If you're running automations that call a model dozens or hundreds of times a day, using the same flagship model for every step is the most common way teams overspend on tokens without getting better output.

The practical split, based on OpenAI's own stated positioning for these tiers, looks like this:

• High-volume classification, tagging, routing, and data extraction: a small/cheap tier (Luna-class) is designed for exactly this. If a task has a clear, narrow goal and doesn't require multi-step reasoning, it's a candidate for the cheapest tier that still hits your accuracy bar.
• Complex, multi-step agent work, coding, and tool-calling chains: a mid tier (Sol-class) is where OpenAI is positioning its factuality gains, which makes it a reasonable default for agent workflows that need real reliability without flagship pricing.
• Judgment calls, ambiguous edge cases, and anything customer-facing where an error is costly: keep the flagship tier (Astra-class) in the loop, either as the default or as an escalation path when the cheaper tier's confidence is low.

We have not independently benchmarked Sol or Luna against Astra or against Claude's tiers for our own automation workloads. Treat vendor-published benchmarks as a starting point for testing, not a substitute for testing on your own data and your own success criteria. The right tier for a given task depends on your accuracy requirements, your volume, and what a mistake actually costs you, and that only shows up when you run your own workload through it.

The one thing to do next

If you're running an automation pipeline that calls the same model for every step regardless of task complexity, audit which steps are high-volume and low-complexity versus which ones need real reasoning. That single change, routing cheap-tier models to the repetitive steps and reserving flagship models for the judgment calls, is usually the fastest way to cut token spend without touching output quality on the steps that matter.

If you want help mapping your current automation stack to the right model tier for each step, talk to ManasFlow about an AI automation build.

FAQ

What are the GPT-6 model tiers?

Three: GPT-6 Astra (flagship), GPT-6 Sol (mid tier, now GPT-6.1 Sol in the API) and GPT-6 Luna (small, high-volume tier). OpenAI has not announced a fourth tier.

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

Price and the work each is built for. Astra costs $10 / $50 per 1M input / output tokens and targets the hardest reasoning and coding. GPT-6.1 Sol costs $2 / $10, and OpenAI describes it as near-Astra performance for complex work. Luna costs $0.10 / $0.50 and is built for summarizing, extraction and quick answers at volume. All three have a 1.05M-token context window.

How much do GPT-6 Sol and Luna cost?

GPT-6.1 Sol costs $2 input, $10 output and $0.10 cached input per 1M tokens. GPT-6 Luna costs $0.10 input, $0.50 output and $0.01 cached input. The Batch tier halves both. Prices from OpenAI's API pricing page on October 23, 2026.

What is GPT-6.1 Sol?

An updated Sol model OpenAI released in the API on September 29, 2026 (gpt-6.1-sol), for complex coding and professional work at a lower cost than Astra. It keeps GPT-6 Sol's $2 / $10 price and 1.05M-token context, and adds multi-agent support in beta through the Responses API. OpenAI's models page now lists it in place of GPT-6 Sol.

Is there a GPT-6 Terra model?

Not from OpenAI. As of October 23, 2026, OpenAI's models and pricing pages list only Astra, Sol (GPT-6.1 Sol) and Luna in the GPT-6 family. Treat "Terra" reports as speculation.

Can free ChatGPT users use GPT-6 Luna?

Yes, in the desktop app. OpenAI's September 22 announcement says Free and Go users can try GPT-6 Luna in the ChatGPT desktop app. Sol and Luna rolled out in ChatGPT Work and Codex for Plus, Pro, Business, Enterprise and Edu users.

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