GPT 6.1 Sol
Neural Network
OpenAI's GPT 6.1 Sol API: a GPT-6 series model for agentic programming, computer use, and large documents.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 050 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- low, medium, high, extra high, max
- Capabilities
- reasoning, function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
import OpenAI from 'openai';
const openai = new OpenAI({
apiKey: '<your bothub access token>',
baseURL: 'https://openai.bothub.chat/v1'
});
// Sync - Text generation
async function main() {
const chatCompletion = await openai.chat.completions.create({
messages: [{ role: 'user', content: 'Say this is a test' }],
model: 'gpt-6.1-sol:batch',
});
}
// Async - Text generation
async function main() {
const stream = await openai.chat.completions.create({
messages: [{ role: 'user', content: 'Say this is a test' }],
model: 'gpt-6.1-sol:batch',
stream: true
});
for await (const chunk of stream) {
const part: string | null = chunk.choices[0].delta?.content ?? null;
}
}
main();
How it works GPT 6.1 Sol?
GPT 6.1 Sol is an update to OpenAI's GPT 6 Sol: a GPT-6 series model positioned below the flagship GPT-6 Astra. Its strengths include agentic programming, computer use, and professional tasks involving large documents, while the batch variant is designed for batch request processing. You can connect it in BotHub without a VPN or foreign card: pay with a Russian card in rubles based on actual usage, and tokens do not expire. With over 250 models in one window and a unified OpenAI-compatible API, you can switch models without rewriting integrations. Companies have access to contracts, invoices, electronic document management, and an admin panel with limits. Developers can use the model to analyze unfamiliar code, refactor, and debug across multiple files. Lawyers and analysts can use it to review long contracts, reports, and regulations to create summaries. For those building agents, the model handles multi-step scenarios involving interfaces and tools. For repetitive request arrays, batch mode eliminates manual runs.Frequently asked questions about GPT 6.1 Sol
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
This is a text model with a 1,050,000 token context, reasoning mode, and function calling. It is suitable for analyzing large documents and codebases, refactoring and debugging, STEM tasks, analytics, and long texts. It accepts text, images, and documents as input.
The output limit is 128,000 tokens per response. This is enough for a voluminous article, detailed technical analysis, large code module, or comprehensive report without splitting the task into dozens of separate requests and manually stitching parts together.
Yes, reasoning mode is supported. The model first outlines the solution path and then provides the result — this helps with math, logic, code analysis, and tasks where a sequence of steps is important rather than a quick, superficial answer.
Yes, both function calling and structured JSON output are supported. The model can be connected to external tools, databases, and services, and the predictable response format simplifies data parsing on your backend without additional parsers.
According to our data, it accepts text, images, and documents as input, including in native format. You can send an interface screenshot, diagram, chart, or PDF file and get a text analysis of the content, a summary, or answers to questions about it.
The model works with requests in Russian, just like other models in this family. The easiest way to check the quality for your tasks is directly in BotHub: access from Russia without a VPN or foreign card, payment in rubles, and one-click switching to another model.