Nemotron-4 340B Instruct (FP8 Quantized)

Nemotron 4 340B Instruct stands out as a robust option for those who need a language model that can handle detailed reasoning and coding tasks. In addition, Built by NVIDIA, Nemotron-4 340B Instruct (FP8 Quantized) focuses on their hardware, which means it runs efficiently on systems equipped with NVIDIA GPUs.

This model supports a context window of 128,000 tokens, allowing it to process long documents or maintain extended conversations without losing track of earlier details. For example, For students and developers, this is particularly useful when working on projects that involve large amounts of text or require step by step problem solving, such as debugging code or analyzing research papers.

Nemotron-4 340B Instruct (FP8 Quantized) capabilities and use cases

In addition, its main capabilities include Reasoning, Code generation, Multilingual support, Function calling and Structured output. For example, common use cases include Academic research, Software development, Content creation, Data analysis and Chatbots.

Who should consider Nemotron-4 340B Instruct (FP8 Quantized)?

In practice, this model may suit Computer science students, Research assistants, Content writers, Developers building chatbots and Data analysis learners. Also, notable strengths include Strong reasoning and problem solving abilities, Supports multiple languages effectively, High token limit for long conversations or documents and Fine tuning and function calling available. However, review trade-offs such as Knowledge cutoff in early 2026 may miss recent developments, Primarily text based; no native image or audio support and Free tier may be insufficient for extensive projects before adopting it.

Nemotron-4 340B Instruct (FP8 Quantized) pricing and access

Meanwhile, Free tier with 10,000 tokens per month; paid plans start at $0.002 per 1,000 input tokens and $0.004 per 1,000 output tokens. Free tier available with 10,000 tokens per month; paid plans start at a few dollars for moderate use.

Official resources and verification

Use the official model website, official documentation, pricing or release source and additional primary source to confirm current availability, limits and pricing. Product details can change after publication, so rely on primary documentation for final decisions.

Compare with other AI models

Next, continue your research in the AI models directory, NVIDIA models and General Purpose Language Model models. Compare providers, pricing, modalities and practical limitations side by side to choose the right model for your workflow.