Sulphur-2-base on AMD/Nvidia GPU Quantized GGUF

Sulphur-2-base on AMD/Nvidia GPU Quantized GGUF

The fastest way to get this model running locally is via Docker.

Review and follow the instructions below.

The installer auto-downloads and deploys the entire model pack.

The automated installation script takes care of everything by tailoring the setup perfectly to your system specs.

📡 Hash Check: 4df1b61d2e68fe0dbdda4ccaa5c91bf4 | 📅 Last Update: 2026-06-25



  • Processor: high single-core performance needed for token latency
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space:70 GB free space for full FP16 weights storage
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

Sulphur-2-base is a next‑generation language model designed to excel in scientific reasoning and code generation. It leverages an enhanced transformer architecture with a 2‑trillion‑parameter base, enabling unprecedented contextual depth. The model incorporates specialized fine‑tuning for chemistry and physics domains, delivering high‑fidelity predictions with reduced hallucinations. Performance benchmarks show a 15% improvement over prior Sulphur variants in multi‑step problem solving. Below is a quick comparison of key specifications against its nearest competitor:

Metric Sulphur-2-base Competitor X
Parameters 2 trillion 1.5 trillion
Domain Accuracy 92% 84%
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