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NVIDIA: Llama 3.1 Nemotron Ultra 253B v1

Llama-3.1-Nemotron-Ultra-253B-v1 is a large language model (LLM) optimized 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.

Context Window

131K

Input Price

$0.6000/M tokens

Output Price

$1.80/M tokens

Modality

text->text

Pricing Breakdown
Cost per million tokens for input and output
Input$0.6000/M tokens
Output$1.80/M tokens

Cost Example: Processing 10,000 input tokens and generating 1,000 output tokens would cost approximately $0.007800

Context Window Size
Maximum tokens the model can process in a single request
Context Window131K tokens
13% of 1M max

~98K

Words Equivalent

~66

Pages of Text

~1311

Code Functions

Best Use Cases
What this model excels at
MathReasoningAnalysisChatConversationAssistant

Related Categories:

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