GPT-6.1 Terra vs Sol: Which OpenAI Model Should You Use?

GPT 6.1 Terra vs Sol is the question everyone building with OpenAI is asking this week. OpenAI launched GPT-6.1 Terra as a fast, cheaper model for computer use, visual reasoning and writing, while GPT-6.1 Sol stays its balanced model for hard agentic coding. Terra costs half as much per token. Sol is still the pick for the toughest code. In the video below I walk through Terra, and on this page I put the two side by side so you can choose the right one for each job.

GPT-6.1 Terra and Sol at a glance

Both models come from OpenAI’s GPT-6 family and both take text and images in and give text out. The differences are in price, speed and what each is tuned for. Here are the specs from OpenAI’s own Terra model page, Sol model page and latest-model guide.

Both support the same main tool set in the Responses API, including web search, file search, code interpreter, hosted shell, apply_patch, skills, computer use, MCP and tool search. Both list Chat Completions too, but tool calling needs the Responses API.

Price: Terra is half the cost

OpenAI says Terra’s standard API prices are 50% lower than GPT-6.1 Sol (and 50% lower than the older GPT-5.6 Terra). The numbers line up: $1 vs $2 for input and $5 vs $10 for output per million tokens. Cached input is $0.05 on Terra and $0.10 on Sol.

The same pricing rules apply to both: Batch and Flex are 50% cheaper than Standard, and prompts over 272K input tokens cost more. Terra’s Fast mode is 2x Standard. If you run high-volume work — OpenAI’s example is reading invoices and typing the details into accounting software — that halving adds up quickly.

It also matters inside ChatGPT Work and Codex. OpenAI says the same plan allowance covers more tasks with Terra, and substantially more than with GPT-6.1 Sol or GPT-6 Astra.

Where GPT-6.1 Terra wins

Terra is the screen-and-eyes model. OpenAI built it for the computer-based work that fills a normal day: filling forms, reading technical drawings, editing videos and drafting proposals. These are OpenAI’s own results from the Terra launch post:

• Computer use. On Agents’ Last Exam, Terra at medium effort performs on par with GPT-6 Astra at one-tenth Astra’s price per token, and scores 15 points above GPT-5.6 Terra at about a third of the cost.
• Speed. OpenAI says Terra completes tasks over three times faster than both GPT-6 Astra and GPT-6.1 Sol.
• Visual reasoning. On MMMU-Pro, Terra nearly matches GPT-6 Astra and GPT-6.1 Sol at much lower cost.
• Desktop apps. On OSWorld 2.1, Terra at medium effort beats GPT-5.6 Terra’s best score at a fraction of the cost per task.
• Fewer mistakes. On OpenAI’s internal set of error-inducing prompts, Terra’s error rate at low effort fell from 53.6% (GPT-5.6 Terra) to 16.7%. At max effort it is 4.3%, which OpenAI says nearly matches Astra and Sol.
• Writing. OpenAI calls out clearer, more natural writing as one of Terra’s strengths.

Terra also supports a none reasoning effort, which Sol doesn’t. That’s handy for quick, simple steps where you want an instant answer and no thinking time.

Where GPT-6.1 Sol wins

OpenAI is direct about this in the Terra post: “For the most complex coding tasks, GPT-6.1 Sol and GPT-6 Astra remain the better choice.” Terra’s coding did improve a lot — it solves 50.3% of Terminal-Bench 4.0 at max effort, more than double GPT-5.6 Terra’s 21.5% — but Sol is the one OpenAI points to for hard code.

Sol’s own numbers back that up. In the GPT-6.1 Sol launch post, OpenAI reports 75.2% on DeepSWE v1.1 at high effort, matching GPT-6 Astra at about a fifth of the cost. In its low-resource languages write-up, OpenAI says Sol migrated COBOL programs with 86.6% success at low effort, rising to 97.9% at higher effort — while noting production work still needs expert review.

Sol also gets Ultrafast mode in Codex for faster token generation, which Terra doesn’t offer. If you live in Codex doing long coding sessions, that’s a real reason to stay on Sol. I cover Sol in more depth in my GPT-6.1 Sol guide and GPT-6.1 Sol coding breakdown.

One result where Terra beats Sol

There’s one benchmark where OpenAI says Terra comes out ahead. On Terminal-Bench-Science 0.1, which tests agents using code for scientific research tasks, Terra at max effort surpasses GPT-6.1 Sol at lower cost. So for science-style data work, Terra is worth testing before you default to Sol.

Everything else OpenAI published for Terra is compared against GPT-5.6 Terra, GPT-6 Astra or Claude Opus 5.5, not scored side by side with Sol. So don’t read the numbers above as a full head-to-head — treat them as OpenAI’s guide to what each model is for.

Which should you pick?

Here’s the simple version, based on what OpenAI says each model is for:

If your work is mostly screen work and writing, start on Terra. If it’s mostly hard engineering, stay on Sol.

How to switch between them

• ChatGPT Work and Codex: Terra is available to Plus, Pro, Enterprise and Edu users. In Codex, pick it with /model, the same way you switch to Sol.
• API: set model to gpt-6.1-terra or gpt-6.1-sol. Use the Responses API if you need tools.
• Moving from Sol to Terra: keep your reasoning effort the same to start, then test lower settings. If you used none on an older model, Terra supports it and Sol doesn’t.
• Test first: OpenAI’s migration guide suggests comparing models on your own representative tasks before switching everything.

Use both together

You don’t have to choose one forever. The smart setup is to let each model do what it’s best at: Terra drives the screen, reads images and writes the copy, while Sol handles the hard code. In an agent setup you can route jobs this way automatically — I show how in my guide to choosing a Hermes subagent model.

Three Terra agents worth setting up first, from my video:

• An admin agent that opens your apps, reads incoming documents and enters the details where they belong.
• A research-and-writing agent that reads screenshots and pages, then drafts the summary or post in plain English.
• A screen-testing agent that clicks through your site or app and reports what breaks.

Then keep Sol on standby for anything that turns into real engineering work.

A note on safety

OpenAI says Terra meets the Critical threshold in cybersecurity under its Preparedness Framework and keeps the protections built for GPT-6 Astra. It also says Terra is more likely to stay within scope, flag limitations and blockers to you, and resist prompt-injection attacks than GPT-5.6 Terra. Computer-use agents still click real buttons, so start them on low-risk tasks and check their work.

My verdict on GPT 6.1 Terra vs Sol

For most everyday agent work — screens, forms, images and writing — Terra is the better buy: half the price, much faster, and built for exactly that job. For the hardest coding, OpenAI itself still points to Sol. Run Terra by default, call in Sol when the code gets serious, and you get the best of GPT 6.1 Terra vs Sol without paying Sol prices for everything.

About Julian Goldie

I’m Julian Goldie — founder of Goldie Agency and the AI Profit Boardroom. I test new AI agents almost every day for 432K+ YouTube subscribers and run Hermes, OpenClaw, OpenCode, Claude and Codex side by side in my own Agent OS. Claim your free strategy session or join the AI Profit Boardroom.

Want another angle? Read the AI Profit Boardroom guide to GPT-6.1 Terra vs Sol.

FAQ: gpt 6.1 terra vs sol

Is GPT-6.1 Terra better than GPT-6.1 Sol?

For computer use, visual reasoning, speed and writing, OpenAI positions Terra as the better value. For the most complex coding, OpenAI says Sol and GPT-6 Astra remain the better choice.

How much cheaper is GPT-6.1 Terra than Sol?

Half the price. Terra is $1 per million input tokens and $5 per million output tokens; Sol is $2 and $10.

Is GPT-6.1 Terra faster than Sol?

Yes. OpenAI says Terra completes tasks over three times faster than both GPT-6 Astra and GPT-6.1 Sol.

Can I use GPT-6.1 Terra in Codex?

Yes. Terra is available to Plus, Pro, Enterprise and Edu users in ChatGPT Work and Codex, and in the API as gpt-6.1-terra.

Does GPT-6.1 Terra support reasoning effort none?

Yes. Terra supports none through max. GPT-6.1 Sol starts at low and doesn’t support none.

Related reading

• GPT-6.1 Sol
• GPT-6.1 Sol Coding
• Hermes Computer Use Skill

Last updated October 2026. This page is a living guide to gpt 6.1 terra vs sol — the facts here move fast and it is updated as they do.