20% Below OpenAI List Rates
Use GPT-6.1 Terra on GPTProto at $0.80 input and $4.00 output per 1M tokens—half the GPTProto rate of GPT-6.1 Sol.
GPT 6.1 Terra
Access OpenAI's GPT-6.1 Terra through GPTProto for visual reasoning, computer use, coding, and natural writing. Get a 1.05M-token context window, adjustable reasoning, and 20% lower token rates with one key shared across 200+ models.
API Usage Examples
curl --request POST "https://gptproto.com/v1/chat/completions" \
--header "Authorization: Bearer $GPTPROTO_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"model": "gpt-6.1-terra",
"messages": [
{
"role": "user",
"content": "Hello"
}
]
}'GPT 6.1 Terra pricing
Chat, coding agents & document work. Priced per 1M tokens — input, cached input and output are billed separately. GPTProto is 20% below official rates.
| Scenario | OpenAI list | OpenRouter | GPTProto | You save / mo |
|---|---|---|---|---|
| Personal10M tokens / mo (4.8M cached) | $13.44 | $14.18 | $10.75 | −$2.69≈ $32.26 / yr |
| Team100M tokens / mo (48M cached) | $134.40 | $141.79 | $107.52 | −$26.88≈ $322.56 / yr |
| Business500M tokens / mo (240M cached) | $672.00 | $708.96 | $537.60 | −$134.40≈ $1612.80 / yr |
Save $0.00 / month
Annual savings ≈ $0.00 · pay as you go
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GPT 6.1 TerraCurrent
OpenAI · $0.8/M input · $4/M output
Bytedance · 262K context · $0.0971/M input · $0.9714/M output
Bytedance · 262K context · $0.0971/M input · $0.9714/M output
Model
Price: GPTProto
vs Official
vs OpenRouter
Context
Stability
GPT 6.1 TerraCurrent
OpenAI
$0.80 / $4.00per 1M tokens
-20%
-24%
—
GPT-6.1 Terra API for Vision, Computer Use, and Agents
Run OpenAI's fast, cost-efficient GPT-6.1 Terra through GPTProto for visual reasoning, computer use, coding, and natural-language work. Keep up to 1.05M tokens of context, choose from six reasoning levels, and pay 20% below OpenAI's standard token rates.
1.05M Context, 128K Output
Provide long task histories, documents, screenshots, and code within a 1,050,000-token context while reserving room for reasoning and up to 128,000 output tokens.
Vision-to-Action Workflows
Use text and image inputs for product matching, technical drawings, application screens, and document workflows. The model can support computer-use agents through a compatible tool-enabled route.
Reasoning from None to Max
Choose none for simpler, latency-sensitive work or raise effort through low, medium, high, xhigh, and max when the task needs deeper analysis.
What Is the GPT-6.1 Terra API?
GPT-6.1 Terra is OpenAI's efficiency-focused GPT-6.1 model, released on October 26, 2026. It is designed for visual reasoning, precise computer use, and clear natural writing. The model accepts text and image inputs and returns text, so it can connect visual understanding to structured analysis, written output, or actions performed by an external agent harness.
This is not only a text-to-text API. Developers can use screenshots, product photos, diagrams, and other image inputs alongside written instructions. OpenAI also lists streaming, function calling, Structured Outputs, and computer use among the model's supported capabilities. Tool calling on OpenAI's service requires the Responses API; confirm the routes and fields exposed by GPTProto in the API Usage tab before moving an existing integration.
GPTProto provides GPT-6.1 Terra API access with one account, one key, and a balance shared across more than 200 supported models. This makes it easier to compare Terra with GPT-6.1 Sol, configure a higher-capability fallback, or test lower-cost alternatives without funding a separate provider account for every model.
| Published specification | GPT-6.1 Terra |
|---|---|
| Developer | OpenAI |
| Release date | October 26, 2026 |
| Model ID | gpt-6.1-terra |
| Input | Text and images |
| Output | Text |
| Context window | 1,050,000 tokens |
| Maximum output | 128,000 tokens |
| Knowledge cutoff | June 1, 2026 |
| Reasoning effort | none, low, medium (default), high, xhigh, max |
| Model features | Streaming, function calling, Structured Outputs |
| Tool calling | Requires the Responses API on OpenAI's service |
| Fine-tuning | Not supported |
GPT-6.1 Terra API Applications
Visual operations and catalog matching. Match product photographs to catalog records, read labels or interface states, and return structured fields for a downstream system. Keep confidence checks and human review around ambiguous images rather than treating every visual match as final.
Computer-use agents. Combine screenshots with tool results so an agent can understand an application state, choose the next action, and verify what changed. Define allowed actions, confirmation gates, timeouts, and completion criteria in the surrounding agent workflow.
Coding and developer workflows. Use GPT-6.1 Terra for routine implementation, UI debugging from screenshots, test generation, code explanation, and bounded repository tasks. Compare difficult work with GPT-6.1 Sol using the same files, tools, and acceptance tests.
Long documents and structured extraction. Use the large context window for specifications, contracts, support histories, research notes, or retrieved document sets. Request Structured Outputs when a downstream application needs predictable fields instead of free-form prose.
What Changed in GPT-6.1 Terra?
OpenAI reports substantial gains over GPT-5.6 Terra in computer use, factuality, and coding. These are provider-reported evaluations, not independent guarantees, so teams should reproduce the comparison on their own images, tools, prompts, and acceptance criteria.
| Evaluation | OpenAI-reported result | Practical reading |
|---|---|---|
| Agents' Last Exam, medium effort | 15 percentage points above GPT-5.6 Terra at about one-third the estimated cost | A stronger candidate for high-volume visual and computer-based work |
| Internal error-inducing prompts, low effort | Error rate fell from 53.6% to 16.7% | Better reported factual reliability at a low reasoning setting |
| Terminal-Bench 4.0, max effort | 50.3% versus GPT-5.6 Terra's published 21.5% | A major coding upgrade, though Sol remains the better starting point for the hardest tasks |
| Task completion speed | More than 3× faster than GPT-6 Astra and GPT-6.1 Sol on the reported agent evaluation | Useful when end-to-end latency matters as much as token price |
GPT-6.1 Terra vs Sol and Other API Models
GPT-6.1 Terra targets the middle of the cost-capability curve: it costs 50% less than GPT-6.1 Sol on GPTProto while retaining the same published 1.05M context window and 128K output limit. Sol remains the safer first test for the most difficult coding and long-horizon reasoning tasks; Terra is the stronger cost-first option for vision, computer use, routine coding, and writing at volume.
| Model on GPTProto | GPTProto input / output per 1M tokens | Use it first when... |
|---|---|---|
| GPT-6.1 Terra | $0.80 / $4.00 | You need visual reasoning, computer use, natural writing, or routine agent work at half Sol's token rate |
| GPT-6.1 Sol | $1.60 / $8.00 | The task is difficult coding, complex professional work, or a long agent run where quality has priority over cost |
| Claude Sonnet 5.5 | $1.80 / $9.00 | You want to evaluate the same coding, agent, document, or vision task on an Anthropic model |
| DeepSeek V4.1 Flash | $0.24 / $0.96 | Low token cost is the priority for text, coding, vision, or agent workloads |
| GLM-5.3 Flash | $0.1275 / $0.425 | You want a low-cost multimodal alternative for text, images, video, or document inputs |
| Gemini 4 Argon | $2.40 / $12.00 | The workflow needs Google-model evaluation or broader native input coverage, including audio and video |
Prices above are the listed GPTProto token rates at the time of writing. Compare models on cost per accepted result—not token price alone—because retries, reasoning tokens, latency, and tool failures can change the total cost of a completed task.
Integration Details to Check Before Moving Traffic
Set the model string to
gpt-6.1-terra; do not reuse a Sol or GPT-5.6 Terra identifier.Start with
reasoning_effort: "medium", OpenAI's default. Testnoneorlowfor routine work, then raise effort only when measured quality gains justify the extra time and generated tokens.Use the Responses API when the workflow requires tool calling. A request that works as plain chat may still need route and response-handling changes before it can run a computer-use or multi-tool loop.
Budget the context window as a combined allowance. Input, retained state, reasoning, and generated output must fit inside the limits; 128K does not guarantee 128K visible answer tokens.
OpenAI applies higher long-context rates to direct API requests above 272K input tokens. Use GPTProto's live Pricing panel as the source of truth for the route and workload you actually run.
Keep a fallback model behind configuration, and switch difficult tasks to GPT-6.1 Sol only when evaluation data justifies the added cost.
When Should You Choose GPT-6.1 Terra?
Choose GPT-6.1 Terra when a workload combines image understanding, application-screen interpretation, structured text output, or computer-based actions and must run below Sol's cost. Test GPT-6.1 Sol for difficult software engineering and long agent runs, or a Flash model when token price dominates. GPTProto keeps these choices behind one key and shared balance.
Compare GPT 6.1 Terra
Side-by-side price, speed and fit against the models people weigh it against.
- Claude Sonnet 5.5 vs GPT-6.1 TerraTerra is the new lower catalog rate. Sonnet stays in the running for graded coding and agent steps.
- Claude Opus 5.5 vs GPT-6.1 TerraTerra is the new lower catalog rate. Opus stays the model for the hard, long-running call.
- Gemini 4 Argon vs GPT-6.1 TerraTerra is the lower catalog rate. Argon stays in the running where the published index is the reason you picked Google.
- Grok 4.7 vs GPT-6.1 TerraOn GPTProto, input and output do not pick the same model. Price the mix you will send.
GPT-6.1 Terra API: Common Questions
How much does the GPT-6.1 Terra API cost on GPTProto?
GPTProto lists Terra at $0.80 per 1M input tokens and $4.00 per 1M output tokens, 20% below OpenAI's standard $1/$5 rates. Use the live Pricing panel for cache and long-context charges.
How do I get a GPT-6.1 Terra API key and use the playground?
Sign in, add balance, create an API key, and test prompts in the Playground. The API Usage section shows the current request format and model string; the same key can access other supported models.
What is the GPT-6.1 Terra API context window?
OpenAI publishes a 1,050,000-token context window and 128,000-token maximum output. Reasoning also consumes generated-token budget, so leave room for reasoning and visible output when sending very large inputs.
Which GPT-6.1 Terra API parameters matter most?
Start with gpt-6.1-terra, reasoning_effort, and your output-token limit. Supported effort values are none, low, medium, high, xhigh, and max; medium is the default. Check API Usage before copying provider-specific fields.
Can reasoning be disabled in GPT-6.1 Terra?
Yes. Terra supports reasoning_effort: "none", unlike Sol. Test it for classification, extraction, or rewriting, then compare with low or medium on latency, token use, and output quality.
Is GPT-6.1 Terra a text-to-text API?
It supports text input and output but also accepts images for visual reasoning. Audio and video are not native inputs; use extracted frames, transcripts, or another model when those formats are required.
Does GPT-6.1 Terra support tool calling and agentic work?
Yes, but route compatibility matters. OpenAI requires the Responses API for tool calling. Your agent harness must still execute tools, return results, enforce permissions, handle retries, and decide when work is complete.
GPT-6.1 Terra vs GPT-6.1 Sol: which should I choose?
Start with Terra for vision, computer use, writing, routine coding, and higher-volume workloads. It is 50% cheaper than Sol at GPTProto's listed rates. Test Sol for the hardest coding and long-horizon reasoning.
How does GPT-6.1 Terra compare with Gemini 4 Argon, Claude Sonnet 5.5, DeepSeek V4.1 Flash, and GLM-5.3 Flash?
Terra combines OpenAI's reported visual and computer-use performance, six reasoning levels, and 1.05M context. Gemini 4 Argon accepts more native input types, Sonnet is the Anthropic alternative, and DeepSeek or GLM Flash costs less. Benchmark identical tasks before choosing.
Does GPTProto provide private GPT-6.1 Terra API access?
Requests use your GPTProto API key. Store it server-side, restrict access, and avoid unnecessary prompt or output logging. Review current data-handling terms and account controls before sending confidential or regulated material.
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