nemotron-3-nano

Nemotron-3-Nano is a new Standard for Efficient, Open, and Intelligent Agentic Models, now updated with a 4B parameter count model.

Araç Kullanımı Akıl Yürütme 4b 30b
Hızlı Kurulum (Ollama kuruluysa)
ollama run nemotron-3-nano

Ollama kurulu değil mi? ollama.com/download — Windows, macOS ve Linux için ücretsiz. İlk çalıştırmada model indirilir, sonrası tamamen çevrimdışıdır.

Varyantlar

Boyut büyüdükçe kalite artar, donanım ihtiyacı yükselir. Başlangıç için küçük varyantı deneyin.

EtiketBoyutBağlamGirdiKomut
latest 24GB 1M Text ollama run nemotron-3-nano:latest
4b 2.8GB 256K Text ollama run nemotron-3-nano:4b
30b 24GB 1M Text ollama run nemotron-3-nano:30b
4b-q8_0 4.2GB 256K Text ollama run nemotron-3-nano:4b-q8_0
4b-bf16 8.0GB 256K Text ollama run nemotron-3-nano:4b-bf16
30b-a3b-q4_K_M 24GB 1M Text ollama run nemotron-3-nano:30b-a3b-q4_K_M
30b-a3b-q8_0 34GB 1M Text ollama run nemotron-3-nano:30b-a3b-q8_0
30b-a3b-fp16 63GB 1M Text ollama run nemotron-3-nano:30b-a3b-fp16
30b-cloud 1M Text ollama run nemotron-3-nano:30b-cloud

Model Detayları ve Benchmarklar (kaynak: ollama.com)

Nemotron-3-Nano

Nemotron 3 Nano 4B

ollama run nemotron-3-nano:4b

Nemotron 3 Nano 30B

ollama run nemotron-3-nano:30b

Ollama’s Cloud

ollama run nemotron-3-nano:30b-cloud

What is Nemotron?

NVIDIA Nemotron™ is a family of open models with open weights, training data, and recipes, delivering leading efficiency and accuracy for building specialized AI agents.

Nemotron 3 Nano 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 configured through a flag in the chat template. If the user prefers the model to provide its final answer without intermediate reasoning traces, it can be configured to do so, albeit with a slight decrease in accuracy for harder prompts that require reasoning. Conversely, allowing the model to generate reasoning traces first generally results in higher-quality final solutions to queries and tasks.

The model employs a hybrid Mixture-of-Experts (MoE) architecture, consisting of 23 Mamba-2 and MoE layers, along with 6 Attention layers. Each MoE layer includes 128 experts plus 1 shared expert, with 6 experts activated per token. The model has 3.5B active parameters and 30B parameters in total.

The supported languages include: English, German, Spanish, French, Italian, and Japanese. Improved using Qwen.

License/Terms of Use

Governing Terms: Use of this model is governed by the NVIDIA Open Model License Agreement.