Sarvam-30B is an advanced Mixture-of-Experts (MoE) model with 2.4B non-embedding active parameters, designed primarily for practical deployment. It combines strong reasoning, reliable coding ability, and best-in-class conversational quality across Indian languages. Sarvam-30B is built to run reliably in resource-constrained environments and can handle multilingual voice calls while performing tool calls.
Sarvam-30B is an advanced Mixture-of-Experts (MoE) model with 2.4B non-embedding active parameters, designed primarily for practical deployment. It combines strong reasoning, reliable coding ability, and best-in-class conversational quality across Indian languages. Sarvam-30B is built to run reliably in resource-constrained environments and can handle multilingual voice calls while performing tool calls. A major focus during training was the Indian context and languages, resulting in state-of-the-art performance across 22 Indian languages for its model size. Sarvam-30B is open-sourced under the Apache License. For more details, see our blog. Architecture The 30B MoE model is designed for throughput and memory efficiency. It uses 19 layers, a dense FFN intermediate_size of 8192, moe_intermediate_size of 1024, top-6 routing, grouped KV heads (num_key_value_heads=4), and an extremely high rope_theta (8e6) for long-context stability without RoPE scaling. It has 128 experts with a shared expert, a routed scaling factor of 2.5, and auxiliary-loss-free router balancing. The 30B model focuses on throughput and memory efficiency through fewer layers, grouped KV attention, and smaller experts. Read more at out blog - https://www.sarvam.ai/blogs/sovereign-models
Apache 2.0
sarvamai
Mixture of Experts (MoE) Language Model
Transformers
Open
Sector Agnostic
04/03/26 15:35:41
59.92 GB
Apache 2.0
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