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Home » Few-Shot » Sulphur-2-base Using Pinokio For Low VRAM (6GB/8GB)

Sulphur-2-base Using Pinokio For Low VRAM (6GB/8GB)

Sulphur-2-base Using Pinokio For Low VRAM (6GB/8GB)

Running this model locally is fastest when deployed through Docker.

Follow the sequence of steps detailed below.

The system automatically triggers a cloud download for all heavy weights.

During setup, the script automatically determines and applies the best settings tailored to your machine.

🔐 Hash sum: 730bd14d95e3028ca5c3343a21ef702e | 📅 Last update: 2026-06-23



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk Space:70 GB free space for full FP16 weights storage
  • Graphics: 12 GB VRAM minimum required for basic quantization

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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