GPT-6.1 Sol vs GPT-6 Astra: Which Should You Use?

At DevDay on September 29, OpenAI released GPT-6.1 Sol at the same API price as its predecessor: $2 per million input tokens and $10 per million output tokens (The Decoder). Astra, the flagship, stayed at $10 / $50. That leaves developers with a real choice between a cheap model that is nearly as good and an expensive one that is the best. For the full event, see our DevDay recap. For how Astra stacks up against Anthropic, see Opus 5.5 vs GPT-6 Astra.

The specs side by side

Specs come from OpenAI's model pages for Sol and Astra and its pricing page, checked on September 29, 2026. One caveat: OpenAI's Sol page is titled GPT-6 Sol and lists the model as gpt-6-sol. I couldn't find a separate GPT-6.1 Sol page or model ID, so confirm which version your API key resolves to.

What the price gap looks like on a real task

Take a typical agent step: 200K tokens of context in, 20K tokens out. Sol costs about $0.60 ($0.40 input plus $0.20 output). Astra costs about $3.00 ($2.00 plus $1.00). Run 5,000 of those steps a month and you're at roughly $3,000 with Sol versus $15,000 with Astra.

So Astra has to save you more than $2.40 per step, in retries or review time, to pay for itself. On easy and medium work it usually won't.

Where Sol is the better pick

Everyday coding and agent work. OpenAI describes Sol as built for complex coding and agentic workflows, with tool use and structured outputs. It supports the same Responses API tools as Astra, including computer use, apply patch, hosted shell and MCP.

Volume. Anything that runs thousands of times a day, like code review passes, triage or test generation, gets 5x cheaper on Sol.

Cheap first attempts. Let Sol try first. If a check fails, retry on Astra. You pay the premium only on the tasks that need it. For the low end of the range, see our Sol, Luna and Grok comparison.

Where Astra is worth paying for

The hardest end-to-end work. OpenAI calls Astra its most capable model, built for complex reasoning, coding, computer use, research and document creation. Those are OpenAI's claims, and I haven't seen an independent Sol-vs-Astra test run under the same conditions.

Speed at any price. Astra Ultrafast is out now at six times the standard rate, or $60 / $300 per million tokens. Sol's Ultrafast version is expected in the coming days, and it will likely be the better deal.

High-stakes tasks. When a wrong answer means a bad deploy or a security hole, the extra $2.40 per step is cheap insurance.

What we don't know yet

Three things aren't settled. First, no independent benchmark compares the two on real repositories. Second, the claim that Sol is close to Astra comes from OpenAI and DevDay press coverage, not third-party tests. Third, GPT-6.1 Astra was reported as withheld over security concerns, so today's Astra is still the GPT-6 version. Treat any 'Sol matches Astra' headline as a hypothesis until you've tested it yourself.

A routing rule you can use this week

1. Default to Sol for coding agents, refactors, code review and tool-heavy workflows.
2. Escalate to Astra when a task fails twice, needs deep research or heavy math, or carries real risk if it's wrong.
3. Use Fast mode or Ultrafast only where latency has a dollar value, like a live coding assistant.
4. Run your own bake-off. Pick 10 real tasks, run both models, and record pass rate, retries and cost per finished task. Pick the model with the lowest cost per finished task, not the best demo. More in our guide to the best AI models for coding.

Bottom line

Sol is the default and Astra is the escalation. At one-fifth of the price, Sol only has to be good enough most of the time, and OpenAI says it is. Save Astra for the tasks where a better answer is worth five times as much.