Skip to content
Figure 51.3: Nemotron 3 Super 120B-A12B · diagram by Sebastian Raschka · click to zoom
Hybrid MoENVIDIA 🇺🇸 · March 11, 2026

Nemotron 3 Super (120B-A12B)

The Super variant scales up Nano and adds both latent experts and native speculative decoding support.

Key detail

Adds latent-space MoE and shared-weight MTP for fast inference.

Total params

120B

Active / token

12B

Context

1M

Fact sheet

Scale
120B total, 12B active (10% active)
Context window
1,000,000 tokens
Decoder type
Hybrid MoE
Attention
Mostly Mamba-2 with a few GQA layers
Layer mix
8 GQA + 40 Mamba-2 + 40 MoE
KV cache / token (bf16)
8 KiB · Very low
License
NVIDIA Nemotron Open Model License
Released

Efficiency

Parameters active per token

10%

12B of 120B weights run for each token.

KV cache per token (bf16)

8 KiB

Smaller than 91% of models in the atlas. How it’s calculated

AA Intelligence Index v4.3.2

Source

12.8

General
22.1
Scientific
12
Coding
18.1
Agents
0.6

Use the ← and → keys to step through releases.

Similar architectures

  • Architecture diagram of Nemotron 3.5 Super VL (120B-A12B)

    NVIDIA, released 2026-10-15. Hybrid MoE decoder, 120B total, 12B active, 1M context. Attention: Mostly Mamba-2 with eight GQA layers.

  • Architecture diagram of Qwen3.8-Flash-Next (125B-A6B)

    Alibaba Cloud, released 2026-08-26. Hybrid MoE decoder, 125B total, 6B active, 256K context. Attention: 3:1 Gated DeltaNet and Qwen Sparse Attention (QSA).

  • Architecture diagram of Ornith 1.5 (35B-A3B)

    Ornith, released 2026-08-23. Hybrid MoE decoder, 35B total, 3B active, 256K context. Attention: 3:1 Gated DeltaNet and Gated Attention.

  • Architecture diagram of Nemotron 3.5 Lightning (30B-A3B)

    NVIDIA, released 2026-08-11. Hybrid MoE decoder, 30B total, 3B active, 1M context. Attention: Mostly Mamba-2 with six GQA layers.

Search the atlas

Jump to a model, concept or page