Available neural network models

ELITE

Show cost in Caps

			Cost in dollars
Model	Max. response length (in tokens)	Context size (in tokens)	Prompt cost (per 1M tokens)	Response cost (per 1M tokens)	Prompt image (for 1k tokens)
gpt-4.1	32 768	1 047 576	2,25	9	0
gpt-4.1-mini	32 768	1 047 576	0,45	1,8	0
gpt-4.1-nano	32 768	1 047 576	0,11	0,45	0
o1-pro	4 096	4 095	168,75	675	0.244
gpt-4.5-preview	16 384	128 000	84,38	168,75	0.122
o4-mini-high	100 000	200 000	1,24	4,95	0.001
o4-mini	100 000	200 000	1,24	4,95	0.001
o3-mini-high	100 000	200 000	1,24	4,95	0

* Our markup on these prices is 5%, which is included in the cost of packages except Basic (Premium and higher)

LLM Request

Cost of a single request in the dashboard

All tariffs

Used tokens + 0.01 USDper 1 request

Special attention: The use of Easy Writer is charged differently. For each text generation, Easy Writer charges an additional 0.1 USD per request + the token cost as specified above for a regular LLM request.

Image Generation

Cost of a single generation by models

MidJourney — Relax

0,03 USD / 20000 CAPSFor 1 generation

MidJourney — Fast

0,06 USD / 40000 CAPSFor 1 generation

MidJourney — Turbo

0,12 USD / 80000 CAPSFor 1 generation

Dall-E

0,03 USD / 20000 CAPSFor 1 generation

Flux

0,06 USD / 40000 CAPSFor 1 generation

Stable Diffusion

0,04 USD / 26250 CAPSFor 1 generation

Web Search

Cost of a single web search usage

All tariffs

Used tokens + 0.01 USDper 1 request

Link Analysis

100 CapsFor 1000 characters

Speech Synthesis

Cost of a single speech synthesis

TTS

7500 CapsFor 1000 characters

TTS HD

15000 CapsFor 1000 characters

Transcription

The cost of one transcription

Whisper

3,000 CapsPer 1 minute

AssemblyAI-nano

2,000 CapsPer 1 minute

AssemblyAI-best

5,500 CapsPer 1 minute

Embeddings

Model embeddings available through our API.

		Cost in Caps	Cost in dollars
Model	Embedding dimension	Prompt cost (per 1 token)	Prompt cost (per 100,000 tokens)
text-embedding-3-largeThe most efficient embedding model	3 072	0,1	0,13
text-embedding-3-smallIncreased performance compared to the 2nd generation ada embedding model	1 536	0,01	0,02
text-embedding-ada-002The most powerful 2nd generation embedding model, replacing 16 first generation models	1 536	0,07	0,1

text-embedding-3-largeThe most efficient embedding model

3 072Embedding dimension

0,1Prompt cost (per 100,000 tokens)

0,13Prompt cost (per 100,000 tokens)

text-embedding-3-smallIncreased performance compared to the 2nd generation ada embedding model

1 536Embedding dimension

0,01Prompt cost (per 100,000 tokens)

0,02Prompt cost (per 100,000 tokens)

text-embedding-ada-002The most powerful 2nd generation embedding model, replacing 16 first generation models

1 536Embedding dimension

0,07Prompt cost (per 100,000 tokens)

0,1Prompt cost (per 100,000 tokens)

Cost of Caps

Caps are the internal currency of the service. The cost of all models is measured in caps. For cheaper models, the cost of one token is approximately equal to one cap, while for more expensive ones it can reach several hundred caps per token. The price of one million caps depends on the tariff: elite tariffs have caps at a lower price than basic ones.

Still have questions?

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What are tokens?

Tokens are units of text processing by the neural network, representing parts of words, entire words, or punctuation marks that determine the cost of requests.

How long will 1 million tokens last?

One million tokens of the GPT-4o model are enough to rewrite “The Brothers Karamazov” by F. M. Dostoevsky.

What to do if I run out of tokens?

Purchase additional Caps in your personal account — https://bothub.chat/profile

Why does the neural network pretend to be another?

The neural network does not know what model it is if it is not specified in the system prompt. The “self-identification” of the model without instruction is influenced by many factors, one of them being the model's data training set.

What is context in a neural network?

Context is the amount of information that the neural network retains in memory during a dialogue, affecting the coherence of responses and understanding of previous requests.

What is the context of different neural network models?

GPT o1 Pro and Claude 3.7 Sonnet support up to 200K tokens, Gemini 2.5 Pro works with 1KK, while Gemini 2.0 Pro supports up to 2KK tokens.

What file formats do models read?

Neural networks process TXT, PDF, DOCX, XLSX, CSV, JSON, XML, HTML, as well as images JPG, PNG, and audio files MP3, MP4.

Can neural networks be used for free?

There are free models with the postfix “:free” and “-exp” that can be used for free through a mini-window on the main page, as well as the model page.

How do neural network models differ from each other?

Models differ in the volume of training data, context size, processing speed, specialization in specific tasks, and ability to work with multimodal content.

How to use models via API?

To integrate models into your applications, you need to obtain an API key in your personal account. More details can be found here: https://bothub.chat/api/documentation/ru.

Can neural networks be used to automate business processes?

Neural networks effectively automate routine tasks of document management, data processing, customer support, and analytics, integrating with existing business systems via API.