MiniMax M2.7 NVFP4

Name: MiniMax M2.7 NVFP4
Author: NVIDIA

by NVIDIA

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

Released April 2026197K context≈ 147,456 words

A compact, quantized text model optimized for efficiency through NVIDIA's NVFP4 precision format. It trades some numerical precision for faster inference and reduced memory footprint, making it practical for deployment on constrained hardware. The open-weight release in safetensors format gives developers direct access to the weights for local use.

Capabilities

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

Long Context

Strong

Instruction Following

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

MiniMax M2.7 NVFP4

by NVIDIA

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

Released April 2026197K context≈ 147,456 words

A compact, quantized text model optimized for efficiency through NVIDIA's NVFP4 precision format. It trades some numerical precision for faster inference and reduced memory footprint, making it practical for deployment on constrained hardware. The open-weight release in safetensors format gives developers direct access to the weights for local use.

Capabilities

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

Long Context

Strong

Instruction Following

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

Glossary

InferenceThe process of running a trained model to generate predictions or outputs from new inputs.Memory FootprintThe amount of RAM or storage space a model requires to run, which is critical for deployment on resource-constrained devices.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.NVFP4 PrecisionA low-precision numerical format that uses 4 bits per weight, developed by NVIDIA to compress models for efficient inference on consumer hardware.PrecisionThe level of numerical detail a model uses to represent its internal values; higher precision means more accurate calculations but requires more memory.QuantizedA technique that reduces a model's size and memory usage by storing weights with lower precision (fewer bits), trading some accuracy for efficiency.SafetensorsA safe, fast file format for storing model weights, designed to prevent code execution vulnerabilities.Safetensors FormatA secure and efficient file format for storing model weights that prioritizes safety and speed when loading models.Text ModelA language model that processes and generates only text, without support for images, audio, or other media types.WeightsThe numerical parameters inside a neural network that determine how it processes input and generates output.