OpenAI: GPT-6.1 Terra
openai/gpt-6.1-terra
Try GPT-6.1 Terra for free in your browser, and add it to your app for free with Puter.js AI API.
Try it free Add to your app// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "openai/gpt-6.1-terra"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "openai/gpt-6.1-terra"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
Model Card
GPT-6.1 Terra is a mid-tier OpenAI model that follows GPT-5.6 Terra in the Terra line. We found no official OpenAI announcement or published benchmarks for it, so details here come from the provider listing and press reports.
It accepts text, image, and file input and returns text. It has a 1,050,000-token context window, 128,000 max output tokens, and supports tool calling. Pricing is $1 per million input tokens and $5 per million output tokens, lower than GPT-6.1 Sol's $2 and $10.
The Information reports that OpenAI intends Terra to outperform GPT-6.1 Sol at a lower price, though we could not verify this. It suits cost-sensitive agentic and document workloads.
Context Window 1M
tokens
Max Output 128K
tokens
Input Cost $1
per million tokens
Output Cost $5
per million tokens
Input file, image, text
modalities
Tool Use Yes
Release Date Oct 27, 2026
Output Speed 92
tokens / sec
Latency 204.39s
time to first token
Try GPT-6.1 Terra for free
Try GPT-6.1 Terra instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How GPT-6.1 Terra performs on standard evaluations.
| Benchmark | Score |
|---|---|
| Humanity's Last Exam Cross-domain reasoning | 46.2% |
| SciCode Scientific programming | 55.1% |
| LCR Long-context reasoning | 82.7% |
Scores sourced from Artificial Analysis.
Find other OpenAI models →
GPT-6.1 Terra Pro
GPT-6.1 Terra Pro is OpenAI's higher-effort configuration of GPT-6.1 Terra, a model in the GPT-6.1 family. Based on how OpenAI handled earlier Pro variants such as GPT-5.6 Terra Pro, it is likely the same underlying model served with reasoning mode set to pro, though we found no OpenAI documentation for the 6.1 release that confirms this. It has a 1,050,000-token context window and 128,000 max output tokens, at $1 per million input tokens and $5 per million output tokens. It accepts text, image, and file input, returns text, and supports tool calling. Terra Pro is intended for harder requests where answer quality matters more than latency. We found no published benchmarks for it.
ChatGPT-6.1 Sol
GPT-6.1 Sol is OpenAI's mid-tier model in the GPT-6 family, released September 29, 2026 as an update to GPT-6 Sol. It sits below the flagship GPT-6 Astra, takes text and image input, supports tool calling, and has a 1,050,000-token context window with 128,000 max output tokens. Pricing is unchanged from GPT-6 Sol at $2 per million input tokens and $10 per million output tokens, while scores are higher. It reaches 75.2% on DeepSWE 1.1 (68.8% for GPT-6 Sol), 71.4% on OSWorld 2.0 (64.4%), and 32.0% on GDP.pdf (28.0%). Its factual error rate at low reasoning effort fell from 11.4% to 7.7%. In one third-party comparison table, GPT-6 Astra scores 74.8% on DeepSWE and 73.5% on OSWorld at roughly five times the price. GPT-6.1 Sol suits coding agents, computer use, document question answering, and workflow automation where cost per task matters.
ChatGPT-6.1 Sol Pro
GPT-6.1 Sol Pro is OpenAI's higher-effort configuration of GPT-6.1 Sol, the mid-tier model in the GPT-6 family. Based on how OpenAI handled GPT-6 Sol Pro, it is likely the same underlying model with reasoning mode set to pro, though OpenAI's documentation for the 6.1 release does not confirm this. It has a 1,050,000-token context window and 128,000 max output tokens, at $2 per million input tokens and $10 per million output tokens. Supported parameters include reasoning effort, tools, tool choice, structured response formats, seed, and streaming. Sol Pro is intended for complex requests such as agentic coding, computer use, and workflow automation, where answer quality matters more than latency. We found no published benchmarks for the Pro configuration itself.
Frequently Asked Questions
You can access GPT-6.1 Terra by OpenAI through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
GPT-6.1 Terra is free to try with a Puter account. Every account includes a free AI allowance, and you can chat with it in the playground on this page. You can upgrade your account anytime for a larger allowance.
GPT-6.1 Terra is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.
| Price per 1M tokens | |
|---|---|
| Input | $1 |
| Output | $5 |
GPT-6.1 Terra was created by OpenAI and released on Oct 27, 2026.
GPT-6.1 Terra supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,100 pages of text.
GPT-6.1 Terra can generate up to 128K tokens in a single response.
GPT-6.1 Terra accepts the following input types: file, image, text. It produces: text.
Yes, GPT-6.1 Terra supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
GPT-6.1 Terra scores 48.1 on the Artificial Analysis Intelligence Index, outperforming 96% of tracked models.
Yes — the GPT-6.1 Terra API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Add GPT-6.1 Terra to your app for free
Developers can integrate GPT-6.1 Terra for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.