Nemotron 3 33B

Overview

NVIDIA's dense 33B model targeting balanced chat, code, and reasoning workloads. Fits a single RTX 4090 at Q4 with a 128k context window.

When to pick this model

• Single-GPU local deployment on a 24GB card (RTX 4090/3090) at Q4
• Mixed workloads spanning chat, code generation, and step-by-step reasoning
• Long-document analysis up to 128k tokens
• Self-hosted alternative to mid-tier API models when data must stay on-prem

VRAM requirements by quantization

VRAM figures include model weights plus a typical 8k KV cache and ~600 MB runtime overhead (Ollama / llama.cpp baseline). Add headroom for higher context lengths.

Strengths

• Dense 33B sized to saturate a 24GB consumer GPU at Q4
• 128k context handles long codebases and reports
• RLHF tuned for reasoning and code, not just chat
• Open weights backed by NVIDIA's research stack

Limitations

• NVIDIA Open Model License has commercial terms worth reviewing carefully
• Gated on Hugging Face (click-through access required)
• Dense 33B is heavier than comparable MoE alternatives at inference

Architecture & training

Architecture: Dense Transformer · 33B parameters · 128k context

Training: NVIDIA Nemotron family, RLHF alignment focused on reasoning and code.

Quick start

ollama run nemotron3

Or use the open-source MCP server to query this model from Claude Desktop, Cursor, or any MCP-compatible client.