Sarvam-30B
Active Parameters
32B
Context Length
128K
Modality
Text
Architecture
Mixture of Experts (MoE)
License
Apache 2.0
Release Date
6 Mar 2026
Knowledge Cutoff
-
Technical Specifications
Total Expert Parameters
2.4B
Number of Experts
128
Active Experts
6
Attention Structure
Grouped-Query Attention
Hidden Dimension Size
4096
Number of Layers
19
Attention Heads
-
Key-Value Heads
4
Activation Function
SwigLU
Normalization
RMS Normalization
Position Embedding
ROPE
Sarvam-30B
Sarvam-30B is an advanced Mixture-of-Experts (MoE) model with 32B total parameters and 2.4B active parameters, designed for practical deployment in resource-constrained environments. Released March 6, 2026 under Apache 2.0 license. Uses 19 layers with 128 experts, top-6 routing, grouped KV attention (4 heads), and extremely high rope_theta (8e6) for long-context stability. Delivers state-of-the-art performance across 22 Indian languages with strong reasoning, reliable coding ability, and best-in-class conversational quality. Optimized for multilingual voice calls with tool calling capabilities, throughput, and memory efficiency.
About Sarvam
Sarvam AI's sovereign foundation models built for India's languages, culture, and context. Released in March 2026, these advanced Mixture-of-Experts (MoE) models offer state-of-the-art performance across 22 Indian languages while maintaining competitive results on global benchmarks. Designed with focus on reasoning, coding, multilingual capabilities, and agentic tasks. Open-sourced under Apache 2.0 license, optimized for practical deployment from resource-constrained environments to high-performance applications.
Other Sarvam Models
Evaluation Benchmarks
No evaluation benchmarks for Sarvam-30B available.
Rankings
Overall Rank
-
Coding Rank
-
GPU Requirements
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Context Size: 1,024 tokens