NVIDIA Nemotron Nano 9B v2 NVFP4

Name: NVIDIA Nemotron Nano 9B v2 NVFP4
Author: NVIDIA

by NVIDIA

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released October 2025131K context≈ 98,304 words

A compact but capable reasoning model that punches above its weight class for its size. It runs in NVFP4 precision, meaning it's optimized for NVIDIA hardware and trades a small amount of numerical fidelity for significantly faster inference and lower memory usage. Its 128K context window is unusually generous for a 9B parameter model, making it practical for long-document tasks without the resource overhead of larger alternatives.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Reasoning & Logic

Moderate

Tool Use

NVIDIA Nemotron Nano 9B v2 NVFP4

by NVIDIA

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released October 2025131K context≈ 98,304 words

A compact but capable reasoning model that punches above its weight class for its size. It runs in NVFP4 precision, meaning it's optimized for NVIDIA hardware and trades a small amount of numerical fidelity for significantly faster inference and lower memory usage. Its 128K context window is unusually generous for a 9B parameter model, making it practical for long-document tasks without the resource overhead of larger alternatives.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Reasoning & Logic

Moderate

Tool Use

Glossary

Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.FidelityThe degree to which a quantized or compressed model preserves the quality and accuracy of the original full-precision model.InferenceThe process of running a trained model to generate predictions or outputs from new inputs.NVFP4 PrecisionA low-precision numerical format that uses 4 bits per weight, developed by NVIDIA to compress models for efficient inference on consumer hardware.NVFP4 PrecisionA low-precision numerical format optimized by NVIDIA that uses fewer bits per number than standard formats, enabling efficient inference on NVIDIA GPUs while maintaining reasonable accuracy.Numerical FidelityThe accuracy and precision with which a model preserves mathematical calculations; lower fidelity means some precision is lost, often as a trade-off for smaller model size.Parameter ModelA neural network described by the number of learnable weights it contains; more parameters generally mean greater capacity to learn complex patterns, but also require more computational resources.PrecisionThe level of numerical detail a model uses to represent its internal values; higher precision means more accurate calculations but requires more memory.ReasoningThe model's ability to work through multi-step logical problems and provide justified answers rather than just pattern-matching.Reasoning ModelA model trained to show explicit step-by-step reasoning and problem-solving logic before producing final answers, rather than jumping directly to conclusions.

Capabilities

Capabilities

Use Case Fit

Glossary