Text Models (LLM)
Overview
The AI/ML API provides access to text-based models, also known as Large Language Models (LLMs), and allows you to interact with them through natural language (that's why a third common name for such models is chat models). These models can be applied to various tasks, enabling the creation of diverse applications using our API. For example, text models can be used to:
Create a system that searches your photos using text prompts.
Act as a psychological supporter.
Play games with you through natural language.
Assist you with coding.
Perform a security assessment (pentests) on servers for vulnerabilities.
Write documentation for your services.
Serve as a grammar corrector for multiple languages with deep context understanding.
And much more.
We support multiple text models. You can find the complete list along with API reference links at the end of the page.
Text Model Specific Capabilities
There are several capabilities of text models that are worth mentioning separately.
Completion allows the model to analyze a given text fragment and predict how it might continue based on the probabilities of the next possible tokens or characters. Chat Completion extends this functionality, enabling a simulated dialogue between the user and the model based on predefined roles (e.g., "strict language teacher" and "student"). A detailed description and examples can be found in our Completion and Chat Completion article.
An evolution of chat completion includes Assistants (preconfigured conversational agents with specific roles) and Threads (a mechanism for maintaining conversation history for context). Examples of this functionality can be found in the Managing Assistants & Threads article.
Function Calling allows a chat model to invoke external programmatic tools (e.g., a function you have written) while generating a response. A detailed description and examples are available in the Function Calling article.
Quick Code Example
We will call the gpt-4o model using the Python programming language and the OpenAI SDK.
If you need a more detailed explanation of how to call a model's API in code, check out our QUICKSTART section.
By running this code example, we received the following response from the chat model:
All Available Text Models (LLM)
Open AI
128000
Open AI
128000
Open AI
128000
Open AI
128000
Open AI
128000
-
Open AI
128000
-
Open AI
128000
Open AI
128000
-
Open AI
8000
Open AI
8000
-
Open AI
8000
-
Open AI
16000
Open AI
16000
Open AI
16000
Open AI
128000
Open AI
128000
-
Open AI
128000
Open AI
128000
-
Open AI
200000
Open AI
128000
Open AI
200000
DeepSeek
128000
DeepSeek
128000
Microsoft
64000
Meta
131000
8000
Meta
128000
-
Gryphe
4000
Mistral AI
64000
Qwen
32000
Mistral AI
64000
Nvidia
128000
NousResearch
32000
-
Meta
128000
Upstage
4000
Meta
131000
Meta
131000
Meta
4100
Qwen
32000
Qwen
131000
-
Meta
9000
Meta
8000
Meta
128000
-
Meta
8000
Meta
4000
Meta
128000
Meta
128000
8000
Mistral AI
32000
Mistral AI
8000
Mistral AI
32000
Meta
128000
-
8000
Gryphe
4000
-
Anthropic
200000
Anthropic
200000
Anthropic
200000
-
Anthropic
200000
-
Anthropic
200000
Anthropic
200000
-
Anthropic
200000
1000000
1000000
32000
1000000
Alibaba Cloud
32000
Alibaba Cloud
131000
Alibaba Cloud
1000000
Alibaba Cloud
32000
Alibaba Cloud
32000
Alibaba Cloud
131000
Mistral AI
32000
X AI
131000
Mistral AI
128000
Open Source
8000
Anthracite
32000
Nvidia
128000
Cohere
128000
AI21 Labs
256000
Mistral AI
256000
Minimax AI
1000000
Minimax AI
245000
-
Next Steps
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