AI Tools Review

NVIDIA: Llama 3.1 Nemotron Ultra 253B v1

By Nvidia

Released: 2025-04-08

API
LLM
RAG
Nvidia
Paid
New

Nvidia Llama 3 1 Nemotron Ultra 253B V1, developed by NVIDIA, features 253B parameters and 131k-token context window. Llama-3.1-Nemotron-Ultra-253B-v1 is a large language model (LLM) optimised for advanced reasoning, human-interactive chat, retrieval-augmented generation (RAG), and tool-calling tasks. Derived from Meta’s Llama-3.1-405B-Instruct, it has been significantly customized using Neural Architecture Search (NAS), resulting in enhanced efficiency, reduced memory usage, and improved inference latency. The model supports a context length of up to 128K tokens and can operate efficiently on an 8x NVIDIA H100 node. Note: you must include `detailed thinking on` in the system prompt to enable reasoning. Please see [Usage Recommendations](https://huggingface.co/nvidia/Llama-3_1-Nemotron-Ultra-253B-v1#quick-start-and-usage-recommendations) for more. Premium pricing at $0.6/1M tokens reflects its advanced capabilities.

Visit NVIDIA: Llama 3.1 Nemotron Ultra 253B v1

AI-Powered

Leverages advanced AI technology to deliver cutting-edge capabilities and results.

Fast & Efficient

Optimized performance ensures quick results without compromising on quality.

Purpose-Built

Specifically designed for llms tasks and workflows.

Nvidia Model Timeline

NVIDIA: Nemotron 3 Nano 30B A3B (free)

256k tokens context

NVIDIA: Nemotron 3 Nano 30B A3B

262k tokens context

NVIDIA: Nemotron Nano 12B 2 VL (free)

128k tokens context

NVIDIA: Nemotron Nano 12B 2 VL

131k tokens context

NVIDIA: Llama 3.3 Nemotron Super 49B V1.5

131k tokens context

NVIDIA: Nemotron Nano 9B V2 (free)

128k tokens context

NVIDIA: Nemotron Nano 9B V2

131k tokens context

NVIDIA: Llama 3.1 Nemotron Ultra 253B v1Current

131k tokens context

NVIDIA: Llama 3.1 Nemotron 70B Instruct

131k tokens context

Specifications

pricing$0.60 / $1.80 (per 1M)
context Window131k tokens

AI Evaluation

4.8
Expert Rating
Text4.9/5
Coding3.5/5

Combines language understanding with search capabilities. Excels at finding and synthesizing information from various sources.

Pros

  • 131k token context window
  • Large-scale 253B architecture
  • Advanced logical reasoning
  • Native function calling

Cons

  • Moderate API costs
  • Requires substantial compute