Skip to content
Figure 38: Sarvam 105B · diagram by Sebastian Raschka · click to zoom
Sparse MoESarvam AI 🇮🇳 · March 3, 2026

Sarvam (105B)

Larger Sarvam variant keeps the sparse MoE layout but switches from GQA to MLA.

Key detail

Large vocabulary and strong Indic language support carried into the larger MLA-based sparse MoE variant.

Total params

105B

Active / token

10B

Context

128K

Fact sheet

Scale
105B total, 10.3B active (9.8% active)
Context window
131,072 tokens
Decoder type
Sparse MoE
Attention
MLA with KV LayerNorm and NoPE + RoPE
Layer mix
32 MLA
KV cache / token (bf16)
36 KiB · Low
License
Apache License 2.0
Released

Efficiency

Parameters active per token

9.8%

10B of 105B weights run for each token.

KV cache per token (bf16)

36 KiB

Smaller than 70% of models in the atlas. How it’s calculated

AA Intelligence Index v4.3.2

Source

8.8

Scientific
5.5

Use the ← and → keys to step through releases.

Similar architectures

  • Architecture diagram of Kolibri-1 (78B)

    Aleph Alpha, released 2026-10-03. Sparse MoE decoder, 78B total, 3.5B active, 256K context. Attention: GQA with QK-Norm and 4:1 sliding-window/global attention.

  • Architecture diagram of Command A+ (218B-A25B)

    Cohere, released 2026-05-20. Sparse MoE decoder, 218B total, 25B active, 128K context. Attention: 16:1 GQA with 3:1 sliding-window/global attention.

  • Architecture diagram of Recursive Flint (40B-A2.5B)

    Recursive, released 2026-10-18. Sparse MoE decoder, 40B total, 2.5B active, 256K context. Attention: GQA with QK-Norm, learned attention sinks, and sliding-window/global attention.

  • Architecture diagram of GLM-4.7 (355B)

    Z.ai, released 2025-12-22. Sparse MoE decoder, 355B total, 32B active, 198K context. Attention: GQA with QK-Norm.

Search the atlas

Jump to a model, concept or page