openai
OpenAI: GPT-6.1 Terra Pro
openai/gpt-6.1-terra-pro
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
Per the OpenRouter catalog, OpenAI's GPT-6.1 Terra Pro (openai/gpt-6.1-terra-pro) is the same underlying model as GPT-6.1 Terra, served in a pro reasoning mode the catalog presents as producing higher-quality responses on complex tasks, at notably higher cost. The listing reports always-on reasoning with five effort levels, a 1,050,000-token context window, and text, image, and file inputs producing text output. These are catalog-reported details rather than measured results; no independent model card or benchmark data was included in this source pack.[1]
Strengths
- The catalog reports a 1,050,000-token context window and text, image, and file inputs with text output, which suits very large or mixed-media inputs.[1]
- Reasoning is enabled by default with five selectable effort levels, from low to max, letting callers trade response depth against cost and latency per the catalog's options.[1]
- The listing reports support for tool calling, structured outputs, seed, response format, and verbosity parameters.[1]
Limitations
- Evidence is catalog-only: benchmark fields are empty, knowledge cutoff is unspecified, and no independent model card was provided, so capabilities need validation on real workloads.[1]
- The catalog itself warns that pro mode spends far more than the base Terra serving, so cost-sensitive use should be tested carefully.[1]
- Reasoning is marked mandatory in the catalog, meaning it cannot be fully disabled for simple tasks that may not need it.[1]
Where to use it
- Complex, multi-step reasoning or analysis tasks where the catalog's pro reasoning mode is intended to help; confirm quality and spend on your own workload.[1]
- Long-document or mixed text, image, and file ingestion workflows that could take advantage of the reported very large context window.[1]
- Agentic or structured-output applications, given the reported tool, structured output, and seed parameters; suitability remains to be verified in practice.[1]
Sources
- [1] OpenRouter catalog · OpenAI: GPT-6.1 Terra ProSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
GPT-6.1 Terra Pro is the same underlying model as [GPT-6.1 Terra](https://openrouter.ai/openai/gpt-6.1-terra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. **Cost note:** pro mode spends far more...
Specifications
- Model ID
- openai/gpt-6.1-terra-pro
- Canonical ID
- openai/gpt-6.1-terra-pro-20261026
- Creator
- openai
- Added to OpenRouter
- 26.10.2026
- Context length
- 1,050,000
- Modality
- text+image+file->text
- Input modalities
- file, image, text
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $1 / out $5
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | reasoning: mandatory · default medium · efforts: max, xhigh, high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: mandatory · default medium · efforts: max, xhigh, high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| OpenAI | 1,050,000 | $0.500 | $2.5 | — | — | — |
| Azure | 1,050,000 | $1 | $5 | — | — | — |
| OpenAI | 1,050,000 | $1 | $5 | — | — | 100% |
| Azure | 1,050,000 | $1.1 | $5.5 | — | — | — |
| Azure | 1,050,000 | $1.2 | $6 | — | — | — |
| OpenAI | 1,050,000 | $2 | $10 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.