GPT-6.1 Terra vs Claude Opus 5.5: price per task, context and when Opus still fits
GPT-6.1 Terra lists at $1 per million input tokens and $5 per million output tokens, one quarter of Claude Opus 5.5's $4 and $20, and both have roughly a one-million-token context window. Whether Terra is cheaper per finished task depends on your workload: OpenAI claims a roughly 9x lower cost per task on one benchmark, but that is OpenAI's own figure and we have not tested either model. Last verified 2026-10-26 (America/Chicago).
Evidence: Reported. Every fact is read from the vendor pages listed under Sources on 2026-10-26 (America/Chicago). We have not run these models for this page.
GPT-6.1 Terra vs Claude Opus 5.5 at a glance
Terra is OpenAI's fast, lower-priced GPT-6.1 model; Opus 5.5 is Anthropic's model for long-running agentic coding and knowledge work. Full facts: GPT-6.1 Terra and Claude Opus 5.5.
| Feature | GPT-6.1 Terra | Claude Opus 5.5 |
|---|---|---|
| Released | 2026-10-26 (OpenAI API changelog) | 2026-09-22 (Anthropic models page) |
| API model id | gpt-6.1-terra | claude-opus-5-5 |
| Input, per 1M tokens | $1 | $4 |
| Output, per 1M tokens | $5 | $20 |
| Cache read, per 1M tokens | $0.05 | $0.20 |
| Cache write, per 1M tokens | $1.25 (30-minute retention) | $5 (5-minute), $8 (1-hour) |
| Batch | Batch and Flex 50% lower than Standard | Batch API 50% discount on input and output |
| Faster tier | Fast mode at 2x Standard price | Fast mode at $8 input / $40 output per 1M tokens, up to 2.5x speed (Claude Code and Claude Platform) |
| Long prompts | Prompts over 272K input tokens: 2x input and cache rates, 1.5x output, for the full request | Anthropic says the full 1M context is included at standard pricing |
| Context window | 1,050,000 tokens (922,000 max input) | 1M tokens |
| Max output | 128,000 tokens | 128K tokens |
| Modalities | Text and image in, text out | Text and images in, text out |
| Knowledge cutoff | Jun 01, 2026 | Jun 2026 (reliable knowledge cutoff) |
| Thinking / effort | Reasoning effort none to max, default medium | Adaptive thinking always on, default effort medium |
| Where it runs | OpenAI API, ChatGPT Work and Codex, GitHub Copilot | Claude API, Amazon Bedrock, Claude Models on Google Cloud, Microsoft Foundry, Claude Platform on AWS; Claude Code; listed in GitHub Copilot |
Sources: OpenAI's Terra model page and API pricing, Anthropic's Opus 5.5 page and pricing page. Standard processing, US dollars.
Get the weekly brief: which AI tools to update, try or skip. Free.
Free. Unsubscribe anytime. No spam. We email a confirmation link first. Privacy
Cost per task, not cost per token
At list price Terra is one quarter of Opus 5.5 on input, output and cache reads. The table below is illustrative arithmetic with identical token counts, which is not how real runs behave: models differ in how many tokens and attempts a task takes.
| Model | Input cost | Output cost | Job total |
|---|---|---|---|
| GPT-6.1 Terra | $0.20 | $0.10 | $0.30 |
| Claude Opus 5.5 | $0.80 | $0.40 | $1.20 |
OpenAI's launch post claims more than that. On its Agents' Last Exam benchmark at max effort it says "Terra is over three times as token efficient as Claude Opus 5.5, and one-fourth its price per token, resulting in a ~9x lower cost per task." That is OpenAI's measurement on OpenAI's chosen benchmark; we have not reproduced it. Anthropic's Opus 5.5 post, published before Terra, makes cost claims against other OpenAI models (for example, matching GPT-6 Astra on Terminal-Bench 4.0 for about 40% of the cost) and has no head-to-head with Terra.
Anthropic's guidance for choosing is to measure completed tasks: see its cost and intelligence guide. Formula: cost per completed task = (input tokens x input price + output tokens x output price) per attempt, times the average number of attempts until your own check passes.
What each vendor claims on shared benchmarks
Both vendors report Terminal-Bench 4.0, a command-line coding benchmark, but with different harnesses, effort settings and vendors running them, so the numbers are not a head-to-head. They are listed so you can see what each company says, not to rank the models.
| Benchmark | GPT-6.1 Terra (OpenAI) | Claude Opus 5.5 (Anthropic) |
|---|---|---|
| Terminal-Bench 4.0 | 50.3% at maximum reasoning effort | 66.4% at xhigh effort |
| Terminal-Bench-Science 0.1 | OpenAI says Terra comes within five points of Opus 5.5 at less than one-fifth the estimated cost, at max reasoning | 58.7% at max effort |
OpenAI also says that for the most complex coding tasks GPT-6.1 Sol and GPT-6 Astra remain better than Terra, which matters if you are comparing Terra with a top-tier Claude model: see GPT-6.1 Terra vs GPT-6.1 Sol.
What the community is reporting
| Reported by | Task | Reported cost and time | Settings stated | Our note |
|---|---|---|---|---|
| EnvolDev on X | "Same Alpine Gold prompt" (task not described in the post) | Opus 5.5: $31.85, 2h 45m. Terra: $4.90, 43m. GPT-6.1 Sol: $3.62, 43m. | None stated | One run, one prompt, no effort or harness settings. Shows Terra and Sol far below Opus on that run, and Sol below Terra, which a per-token price comparison would not predict. |
We include only posts that name the models and give cost and time. Other community runs we saw did not state the task or settings and are left out.
When Opus 5.5 is still the safer pick, and when Terra is enough
Editorial rules of thumb from the vendors' own guidance, not test results.
- Terra is enough when the task is scoped and checkable: OpenAI's model-selection guide points Terra at concise writing from supplied material, computer-use tasks with a defined outcome and scoped code fixes.
- Opus 5.5 is the safer starting point for long, sprawling agent work: Anthropic's models overview says to start with Opus 5.5 for most workloads, and describes it as built for long-running agentic coding and knowledge work.
- Very long prompts favor Opus on price structure: Terra bills the whole request at 2x input and 1.5x output above 272K input tokens, while Anthropic says Opus 5.5 includes the full 1M context at standard pricing.
- Already inside a Claude-only tool? Claude Code is built around Claude models, so Terra there is a gateway question, not a setting. See our availability guide.
- Cheapest sensible plan: run both on your own twenty real tasks, record cost and pass rate, and decide on cost per passed task. Our best LLM for coding page lists dated, sourced benchmark numbers.
What we have not tested
We have not run either model for this comparison. No cost, speed, accuracy or token-count number here is ours: every figure is from the vendor pages and posts linked under Sources, and the community row is one user's unverified claim.
Latest news briefs on these models
- OpenAI GPT-6.1 Terra: a $1/$5 computer-use model, and what the launch post leaves out (Reported; first seen 2026-10-26 19:05 UTC)
FAQ
Is GPT-6.1 Terra cheaper than Claude Opus 5.5?
Per token, yes: Terra lists at $1 input and $5 output per million tokens against $4 and $20 for Opus 5.5, from the vendors' pages on 2026-10-26. Per finished task depends on token use and retries, which we have not measured.
Is GPT-6.1 Terra as good as Claude Opus 5.5 at coding?
We cannot say. OpenAI reports 50.3% on Terminal-Bench 4.0 for Terra and Anthropic reports 66.4% for Opus 5.5, but each vendor ran its own setup, so the figures are not a head-to-head. OpenAI itself says GPT-6.1 Sol and GPT-6 Astra remain better than Terra for the most complex coding.
Can I use GPT-6.1 Terra inside Claude Code?
Not natively as far as Anthropic's docs show. Claude Code's model docs list Claude aliases, and say ANTHROPIC_BASE_URL changes where requests are sent, not which model answers them. Whether a particular gateway can route to Terra is not something we confirmed.
Does Opus 5.5 still lead on long agent runs?
Anthropic positions Opus 5.5 for long-running agentic coding and knowledge work and recommends starting with it for most workloads. We found no independent long-run comparison with Terra, so treat that as Anthropic's positioning, not a measured lead.
What does cost per task mean?
The total spend to get one task to a result you accept: tokens in and out per attempt at list price, times the number of attempts. A cheaper model that needs three attempts can cost more than an expensive model that needs one.
Sources
- OpenAI API: GPT-6.1 Terra model page (fetched 2026-10-26)
- OpenAI API pricing (fetched 2026-10-26)
- OpenAI: Introducing GPT-6.1 Terra (Internet Archive capture; openai.com blocks scripted fetches) (fetched 2026-10-26)
- OpenAI: model selection guide (fetched 2026-10-26)
- Anthropic: Claude Opus 5.5 model page (fetched 2026-10-26)
- Anthropic: models overview (fetched 2026-10-26)
- Anthropic: pricing (fetched 2026-10-26)
- Anthropic: Introducing Claude Opus 5.5 (fetched 2026-10-26)
- Anthropic: optimizing for cost and intelligence (fetched 2026-10-26)
- Claude Code docs: model configuration (fetched 2026-10-26)
- EnvolDev on X: Opus 5.5 vs Sol vs Terra (one user's unverified run) (fetched 2026-10-26)
Related
Page history
- : First published. OpenAI and Anthropic model pages, pricing pages and launch posts read on this date; nothing was run.
Markdown version for agents: /compare/gpt-6-1-terra-vs-claude-opus-5-5.md
Free · weekly · about six minutes
Get The Weekly Verdict, free
What shipped this week, what is worth switching to, and what to ignore. We run what we can and label what we only read.
- One email a week. Each release gets one call: update now, worth a look, or skip.
- Every claim shows its evidence. Reported means we read the sources; Tested means we ran it, with the exact scope and the failures left in.
- A free AI Tools Cheat Sheet (web page and printable PDF) lands in your inbox when you confirm.
Free. Unsubscribe anytime. No spam. We email a confirmation link first and add you only after you click it. We use your email only to send this newsletter and never sell it. Privacy