GraySoft
Download guIDE →
Model Comparison

ggml-org/gemma-4-26b-a4b-it-ggufvsnvidia/nvidia-nemotron-3-nano-4b-gguf

Side-by-side comparison of ggml-org/gemma-4-26b-a4b-it-gguf and nvidia/nvidia-nemotron-3-nano-4b-gguf: downloads, license, context length, tasks, and benchmarks.

ggml-org/gemma-4-26b-a4b-it-gguf

ggml-org · —

# gemma-4-26B-A4B-it-GGUF Recommended way to run this model: ``sh llama-server -hf ggml-org/gemma-4-26B-A4B-it-GGUF `` Then, access http://localhost:8080

nvidia/nvidia-nemotron-3-nano-4b-gguf

nvidia · text-generation

**Model Developer:** NVIDIA Corporation **Model Dates:** Dec 2025 \- Jan 2026 **Data Freshness:** September 2024 The pretraining data has a cutoff date of September 2024\.

Side-by-side Specifications

ggml-org/gemma-4-26b-a4b-it-ggufnvidia/nvidia-nemotron-3-nano-4b-gguf
Authorggml-orgnvidia
Pipeline Task—text-generation
Library—transformers
Downloads238,05526,805
Likes52118
LicenseUnknownUnknown
Context Length——
Created2026-04-012026-03-07
Last Modified2026-04-122026-03-16
Tags
ggufbase_model:google/gemma-4-26B-A4B-itbase_model:quantized:google/gemma-4-26B-A4B-itendpoints_compatibleregion:usconversational
transformersggufnvidiapytorchtext-generationendataset:nvidia/Nemotron-CC-v2dataset:nvidia/Nemotron-Post-Training-Dataset-v2dataset:nvidia/Nemotron-Science-v1dataset:nvidia/Nemotron-Instruction-Following-Chat-v1

View full details: ggml-org/gemma-4-26b-a4b-it-gguf · nvidia/nvidia-nemotron-3-nano-4b-gguf