GPT 6.1 Sol Pro
Neural Network
GPT 6.1 Sol Pro is an OpenAI model with pro reasoning for complex tasks: chat and GPT 6.1 Sol Pro API in BotHub.
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-pro: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-pro: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 Pro?
GPT 6.1 Sol Pro is the same OpenAI model as GPT 6.1 Sol, but with pro reasoning mode: for complex tasks, it builds longer chains of thought and provides higher quality answers. The trade-off is significantly higher token consumption for reasoning, so pro should be enabled where results matter more than speed. The batch version is convenient when requests can be queued and answers retrieved later. In BotHub, the model is available without VPN or foreign cards; payment is via Russian cards in rubles, pay-as-you-go for tokens that do not expire. Over 250 other models are available in one window: you can switch and compare answers, and a unified OpenAI-compatible API allows changing models in code without rewriting integrations. Dialogs are encrypted with AES-GCM and not saved. Companies have access to contracts, invoices, EDI, and an admin panel with limits. Use GPT 6.1 Sol Pro for multi-step analytics, design, and code refactoring with explanations, checking calculations and proofs in STEM, as well as for analyzing large technical materials in batch mode.Frequently asked questions about GPT 6.1 Sol Pro
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.
It is a text model with reasoning and a context window of up to 1,050,000 tokens. It is suitable for analyzing large documents and codebases, refactoring and debugging, STEM tasks, analytics, and working with agents. It accepts text, images, and documents as input.
The maximum response length is up to 128,000 tokens. This is enough for a voluminous technical document, a detailed code analysis, or a long structured report without splitting it into parts. If the response hits the limit, ask it to continue from the next fragment.
Yes, the reasoning mode is confirmed. The model consistently analyzes the task conditions before the final answer, which helps with math, logic, multi-step data analysis, and finding errors in code. For simple queries, such analysis is usually not required.
Yes, the model supports function calling and structured JSON output. This is convenient for agents, integrations with external services, and parsing responses on your application side. A unified OpenAI-compatible API is available in BotHub, so switching between models does not require rewriting code.
Text, images, and documents are accepted as input, including in native formats. You can send a screenshot of an interface, a diagram, a chart, or a PDF and ask to analyze the content. The model returns the answer in text. Audio and video uploads are not noted in our data.
The model is designed for multilingual work, so it processes Russian-language queries correctly: it analyzes documents, formulates texts, and explains code. For complex tasks, it is useful to provide detailed context and specify the required response format — the result will be noticeably more accurate.