nvidia / text-generation updated 6 months ago

NVIDIA-Nemotron-Nano-9B-v2-FP8

Name: NVIDIA-Nemotron-Nano-9B-v2-FP8
Author: nvidia

NVIDIA-Nemotron-Nano-9B-v2-FP8 is a quantized version of NVIDIA-Nemotron-Nano-9B-v2 and is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be controlled via a system prompt....

Params

8.9 B

Context

131,072

Downloads 30d

171 K

Likes

Licence: other Not gated SAFETENSORS 6 languages View on Hugging Face ↗

Download history

tracking started — chart appears after 7 days of snapshots (1 recorded)

171 K downloads in the last 30 days

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	f8_e4m3	10.3 GB	13.1 GB	✅ Runs comfortably
model.safetensors (bf16, full)	bf16 + 128K ctx	10.3 GB	33.1 GB	❌ Won’t fit

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub

~ · curl · api/v1

$ curl -s https://aimodelscomparison.com/api/v1/models/nvidia-nemotron-nano-9b-v2-fp8
{
  "hf_id": "nvidia/NVIDIA-Nemotron-Nano-9B-v2-FP8",
  "params_b": 8.89,
  "context_length": 131072,
  "license": { "id": "other", "commercial": "unknown" },
  "downloads_30d": 170949,
  "vram_estimates": [
    { "quant": "f8_e4m3", "gb": 13.1 }
  ],
  "updated_at": "2026-08-07T01:00:36Z"
}

est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture: NemotronHForCausalLM
Parameters: 8.9 B
Tensor type: F8_E4M3
Context length: 131,072
Vocabulary: 131,072
Layers / heads: 56 / 40
Licence: other
First seen on the Hub: 2025-09-22
Base model: NVIDIA-Nemotron-Nano-9B-v2
Training datasets: nvidia/Nemotron-Post-Training-Dataset-v1, nvidia/Nemotron-Post-Training-Dataset-v2, nvidia/Nemotron-Pretraining-Dataset-sample, nvidia/Nemotron-CC-v2, nvidia/Nemotron-CC-Math-v1, nvidia/Nemotron-Pretraining-SFT-v1
Added to our catalog: 2026-08-07

Family

Base model and the most-downloaded derivatives in the catalog.

Base NVIDIA-Nemotron-Nano-9B-v2 nvidia 310 K

Appears in

Best open coding models Commercial-use text models Models that fit in 12 GB