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What is Sarvam 30B?

Sarvam-30B is a cutting-edge open-source language model designed as a robust platform for real-time conversational AI and intricate reasoning tasks, highlighting its effectiveness in multilingual environments and practical applications. With its impressive 30 billion parameters, the model leverages a Mixture-of-Experts (MoE) approach that activates only a fraction of its parameters for each interaction, enabling high efficiency and minimal latency, making it ideal for use in resource-constrained settings such as local devices and edge computing systems. It stands out in a variety of conversational scenarios, programming challenges, and logical reasoning tasks, delivering remarkable performance in more than 20 Indian languages, which highlights its versatility for multilingual use and voice recognition systems. Its dual-tier architecture positions it as a rapid and easily deployable "conversational workhorse," employing MoE strategies to reduce computational demands while maintaining top-notch performance. This innovative model not only improves the overall user experience but also expands its accessibility across a wide range of linguistic contexts, making it a valuable tool for developers and businesses aiming to engage diverse audiences effectively. Additionally, Sarvam-30B's design allows for continuous improvement and adaptation, ensuring that it remains relevant in the ever-evolving landscape of AI technology.

What is DeepSeek-V2?

DeepSeek-V2 represents an advanced Mixture-of-Experts (MoE) language model created by DeepSeek-AI, recognized for its economical training and superior inference efficiency. This model features a staggering 236 billion parameters, engaging only 21 billion for each token, and can manage a context length stretching up to 128K tokens. It employs sophisticated architectures like Multi-head Latent Attention (MLA) to enhance inference by reducing the Key-Value (KV) cache and utilizes DeepSeekMoE for cost-effective training through sparse computations. When compared to its earlier version, DeepSeek 67B, this model exhibits substantial advancements, boasting a 42.5% decrease in training costs, a 93.3% reduction in KV cache size, and a remarkable 5.76-fold increase in generation speed. With training based on an extensive dataset of 8.1 trillion tokens, DeepSeek-V2 showcases outstanding proficiency in language understanding, programming, and reasoning tasks, thereby establishing itself as a premier open-source model in the current landscape. Its groundbreaking methodology not only enhances performance but also sets unprecedented standards in the realm of artificial intelligence, inspiring future innovations in the field.

Media

Media

Integrations Supported

Hugging Face
Mimasa AI
Sarvam AI

Integrations Supported

SiliconFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

Free
Open source
Free Version

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
On-Prem
Linux

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Sarvam

Date Founded

2023

Company Location

India

Company Website

www.sarvam.ai/blogs/sarvam-30b-105b

Company Facts

Organization Name

DeepSeek

Date Founded

2023

Company Location

China

Company Website

deepseek.com

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

Open-Weight AI Models

Not specified

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