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Model Comparison

ggml-org/gemma-4-31b-it-ggufvsunsloth/nvidia-nemotron-3-nano-4b-gguf

Side-by-side comparison of ggml-org/gemma-4-31b-it-gguf and unsloth/nvidia-nemotron-3-nano-4b-gguf: downloads, license, context length, tasks, and benchmarks.

ggml-org/gemma-4-31b-it-gguf

ggml-org · —

# gemma-4-31B-it-GGUF Recommended way to run this model: ``sh llama-server -hf ggml-org/gemma-4-31B-it-GGUF `` Then, access http://localhost:8080

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

unsloth · text-generation

See Unsloth Dynamic 2.0 GGUFs for our quantization benchmarks. --- # NVIDIA-Nemotron-3-Nano-4B-BF16 **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-4-31b-it-ggufunsloth/nvidia-nemotron-3-nano-4b-gguf
Authorggml-orgunsloth
Pipeline Task—text-generation
Library——
Downloads52,52127,504
Likes3453
LicenseUnknownUnknown
Context Length——
Created2026-04-012026-03-16
Last Modified2026-04-122026-03-17
Tags
ggufbase_model:google/gemma-4-31B-itbase_model:quantized:google/gemma-4-31B-itendpoints_compatibleregion:usconversational
ggufnvidiapytorchtext-generationenarxiv:2511.16664arxiv:2504.03624arxiv:2512.20856arxiv:2512.20848arxiv:2412.02595

View full details: ggml-org/gemma-4-31b-it-gguf · unsloth/nvidia-nemotron-3-nano-4b-gguf