I Re-Priced My Agent Stack on GPT-6.1 Terra: Here's the Routing Rule I'd Actually Ship

OpenAI launched GPT-6.1 Terra on October 26, 2026, and if you build agents for a living, the interesting question is not "is it smart?" It is "where does it sit in my routing table?"

After reading OpenAI's own numbers as reported on October 26-27, my answer is: Terra becomes the default tier, and the flagships become the exception. Here is the reasoning, with the numbers that justify it.

The default tier, priced like one

Terra's API pricing is $1 per million input tokens, $0.05 per million cached input tokens, and $5 per million output tokens - 50% below GPT-5.6 Terra and GPT-6.1 Sol.

Standard rates cover prompts up to 272,000 input tokens; beyond that, input and cache rates double and output costs 1.5x for the full request.

It is available in ChatGPT Work and Codex for Plus, Pro, Enterprise and Edu users, and via the API as gpt-6.1-terra.

Price alone would not move me. Price plus speed plus accuracy does. Terra runs tasks more than three times faster than GPT-6 Astra and GPT-6.1 Sol.

On Agents' Last Exam - professional work such as turning architectural drawings into 3D models or reviewing film scenes into time-coded logs - it beats its predecessor by 15 points at medium reasoning effort, at about a third of the cost, matching Astra at roughly a tenth of the token price.

On OSWorld 2.1, multi-step desktop-app work, it beats its predecessor's best score at medium effort and costs less per task.

The routing rule

Here is the rule I would ship this week:

• Terra by default for the workday bulk: invoice intake, form filling, document processing, inbox triage, proposal drafts, screenshot and drawing interpretation, and routine coding - scripts, fixes, refactors, tests.
• Sol or Astra on exception for complex coding and the hardest reasoning. Terra's Terminal-Bench 4.0 score is 50.3% at maximum effort - more than double its predecessor's 21.5% - but OpenAI itself says Sol and Astra are better for complex coding. Believe the vendor on its own product's limits.
• Effort as a dial, not a setting. Start bulk tasks at medium effort. Escalate to maximum effort only where the error rate matters, because the error numbers justify that dial: on OpenAI's error-inducing internal test, Terra's error rate is 16.7% at low effort (down from 53.6% for the predecessor) and 4.3% at maximum effort - comparable to the flagships.

That third point is the one most routing layers get wrong. They route by model, once, at design time. Terra rewards routing by model and effort, per task, at runtime. A form-fill at medium effort and a contract-summary at maximum effort are different jobs even when they use the same model.

Two tests before you widen autonomy

Terra's alignment claims are the part I would verify before trusting it with a computer. OpenAI says it stays within scope, discloses limitations and blockers honestly, and resists prompt injection in testing. For a computer-use model, those are not nice-to-haves - they are the security boundary.

Test one: put an instruction inside a document that contradicts your instruction, and see whether Terra follows the document or you. Test two: give it a task with a deliberate blocker and see whether it reports the blocker or invents a completion.

If it passes both on your data, widen autonomy gradually. If it fails either, keep the human approval gate - especially for money, legal, or irreversible actions. A 4.3% error rate at maximum effort is excellent for this tier, and it is still an error rate.

Measure cost per finished task

The metric that matters after the switch is not cost per token. It is cost per completed task, including retries and corrections. Terra's speed and accuracy gains compound there: fewer retries, fewer human corrections, lower total cost even before the 50% price cut.

Run your five most common tasks through Terra for a week, log completion rate, error rate, and cost per finished task at medium and maximum effort, and let that table - not the launch blog - set your permanent routing.

Terra is not the model you show off. It is the model you leave running all day. Priced and performing like this, that is exactly where it belongs: as the default, with flagships reserved for the work that actually needs them.

Sources: OpenAI GPT-6.1 Terra launch (October 26, 2026), as reported by NewsBytes, Okay News, and MoneyToday (October 27, 2026). Benchmark figures are OpenAI's own reported evaluations. Author: Shivam Kumar, Founder, VisionQuantech.