diff --git a/reference/nemotron-3-super-running-parameters.md b/reference/nemotron-3-super-running-parameters.md
new file mode 100644
index 0000000..582cd02
--- /dev/null
+++ b/reference/nemotron-3-super-running-parameters.md
@@ -0,0 +1,233 @@
+---
+created: '2026-04-09T18:07:12+00:00'
+id: 2a98c58e-a3e3-429b-87b0-dd9c199a6e91
+keywords:
+- Nemotron 3 Super
+- NVIDIA
+- 120B-A12B
+- temperature
+- top_p
+- min_p
+- GGUF
+- quantization
+- UD-Q4_K_XL
+- NoPE
+- 1M context
+- llama.cpp
+- llama-server
+- MoE
+- 12B active
+- tool calling
+- reasoning tokens
+- NVFP4
+- FP8
+- BF16
+links: []
+modified: '2026-04-09T18:07:12+00:00'
+summary: Optimal running parameters for NVIDIA's Nemotron 3 Super (120B-A12B MoE),
+  covering inference settings for general chat vs tool calling, hardware requirements,
+  NoPE context extension, reasoning token handling, GGUF/NVFP4/FP8 formats, and llama.cpp
+  example commands.
+tags:
+- reference
+- nemotron-3
+- nvidia
+- llm
+- inference
+- llama-cpp
+- local-ai
+title: NVIDIA Nemotron 3 Super — Optimal Running Parameters
+---
+
+# NVIDIA Nemotron 3 Super — Optimal Running Parameters
+
+A reference for optimally running NVIDIA's Nemotron 3 Super (120B-A12B) hybrid reasoning MoE model locally.
+
+## Model Overview
+
+| Property | Value |
+|---|---|
+| Architecture | MoE — 120B total, **12B active parameters** |
+| Max Context | **1M tokens** (default 262,144) |
+| Positional Embeddings | **NoPE** — no explicit positional embeddings; YaRN not needed |
+| Reasoning Tokens | `<think)>` (token ID 12), `</think)>` (token ID 13) |
+| Best For | Multi-agent AI, high-efficiency reasoning, coding, math, agentic workflows |
+| Performance Tier | Leads its size class on AIME 2025, Terminal Bench, SWE-Bench Verified; highest throughput |
+
+## Recommended Inference Parameters
+
+NVIDIA recommends two parameter profiles:
+
+### General Chat / Instruction
+
+| Parameter | Value |
+|---|---|
+| `temperature` | **1.0** |
+| `top_p` | **1.0** |
+
+### Tool Calling
+
+| Parameter | Value |
+|---|---|
+| `temperature` | **0.6** |
+| `top_p` | **0.95** |
+
+### Additional Settings
+
+| Setting | Value | Notes |
+|---|---|---|
+| `max_new_tokens` | **32,768 – 262,144** | Standard prompts; max 1M |
+| `min_p` | **0.01** | Used in llama-server deployment |
+| `--prio` | **2** or **3** | Priority scheduling in llama.cpp |
+| `--seed` | **3407** | Reproducibility |
+| `--special` | (flag) | Needed to see reasoning tokens |
+| `--verbose-prompt` | (flag) | Needed to see `<think)>` since it's prepended |
+
+### Quick Reference — One-Liners
+
+**General chat/instruction:**
+```
+temperature=1.0, top_p=1.0
+```
+
+**Tool calling:**
+```
+temperature=0.6, top_p=0.95
+```
+
+## Hardware Requirements (Total Memory: RAM + VRAM, or Unified Memory)
+
+| Precision | Memory Required |
+|---|---|
+| 2-bit (UD-Q2_K_XL) | ~32–36 GB |
+| **4-bit (UD-Q4_K_XL)** | **~64–72 GB** |
+| 8-bit | ~128 GB |
+| BF16 | ~240 GB |
+
+> **Rule of thumb:** Total available memory should exceed the quantized model size. If it doesn't, llama.cpp can offload to SSD/HDD but inference will be slower.
+
+### Quantization Recommendations
+
+- **Minimum recommended:** **UD-Q2_K_XL** (Dynamic 2-bit) to balance size and accuracy.
+- **Recommended starting point:** **UD-Q4_K_XL** (Dynamic 4-bit) — fits 64–72GB devices.
+- Available in multiple formats: GGUF, NVFP4, FP8, BF16.
+
+## Context Window Management
+
+| Setting | Value |
+|---|---|
+| Native max context | **1M tokens** |
+| Default context | **262,144** (256K) |
+| Recommended starting context | **16,384** (16K) or **32,768** (32K) |
+
+> ⚠️ Setting context to 1M may trigger **CUDA OOM and crash** — increase gradually as RAM/VRAM allows.
+
+### NoPE — No Positional Embeddings
+
+Because Nemotron 3 was trained with **NoPE**:
+- Extend context by simply changing `max_position_embeddings`.
+- **YaRN is NOT needed** for context extension.
+
+## Chat Template Format
+
+Nemotron 3 uses ChatML-style format:
+
+```
+<|im_start|>system\n<|im_end|>\n
+<|im_start|>user\n{message}<|im_end|>\n
+<|im_start|>assistant\n<think)>{reasoning}</think)>{answer}<|im_end|>\n
+```
+
+### Reasoning Tokens
+
+- `<think)>` = token ID **12**
+- `</think)>` = token ID **13**
+- Use `--special` to see tokens, `--verbose-prompt` to see the prepended `<think)>`.
+
+## Example llama.cpp Commands
+
+### General Instruction (4-bit)
+
+```bash
+./llama.cpp/llama-cli \
+    -hf unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-GGUF:UD-Q4_K_XL \
+    --ctx-size 16384 \
+    --temp 1.0 --top-p 1.0
+```
+
+### Tool Calling (4-bit)
+
+```bash
+./llama.cpp/llama-cli \
+    -hf unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-GGUF:UD-Q4_K_XL \
+    --ctx-size 32768 \
+    --temp 0.6 --top-p 0.95
+```
+
+### Conversation Mode (Local GGUF)
+
+```bash
+./llama.cpp/llama-cli \
+    --model unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-GGUF/UD-Q4_K_XL/NVIDIA-Nemotron-3-Super-120B-A12B-UD-Q4_K_XL-00001-of-00003.gguf \
+    --ctx-size 16384 \
+    --seed 3407 \
+    --prio 2 \
+    --temp 0.6 \
+    --top-p 0.95
+```
+
+### llama-server Deployment
+
+```bash
+./llama.cpp/llama-server \
+    --model unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-GGUF/UD-Q4_K_XL/NVIDIA-Nemotron-3-Super-120B-A12B-UD-Q4_K_XL-00001-of-00003.gguf \
+    --alias "unsloth/NVIDIA-Nemotron-3-Super-120B-A12B" \
+    --prio 3 \
+    --min_p 0.01 \
+    --temp 0.6 --top-p 0.95 \
+    --ctx-size 16384 \
+    --port 8001
+```
+
+### OpenAI-Compatible Client (with Reasoning Output)
+
+```python
+from openai import OpenAI
+
+openai_client = OpenAI(
+    base_url = "http://127.0.0.1:8001/v1",
+    api_key = "sk-no-key-required",
+)
+
+completion = openai_client.chat.completions.create(
+    model = "unsloth/NVIDIA-Nemotron-3-Super-120B-A12B",
+    messages = [{"role": "user", "content": "What is 2+2?"}],
+)
+
+# Access both reasoning and final answer
+print(completion.choices[0].message.reasoning_content)
+print(completion.choices[0].message.content)
+```
+
+> **Note:** Unlike some models, Nemotron 3 Super exposes reasoning content separately via `reasoning_content` in the OpenAI-compatible API.
+
+## Fine-Tuning Notes
+
+- **bf16 LoRA** works on **256GB VRAM** (multi-GPU setup).
+- Router-layer fine-tuning is **disabled by default** for stability.
+- For multi-GPU, use `device_map = "balanced"` or follow Unsloth's multiGPU guide.
+- To retain reasoning capabilities in fine-tuning, use at least **75% reasoning** and **25% non-reasoning** data.
+
+## Available Formats
+
+| Format | Link |
+|---|---|
+| GGUF (Dynamic quantization) | [unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-GGUF](https://huggingface.co/unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-GGUF) |
+| NVFP4 | [unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4](https://huggingface.co/unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4) |
+| FP8 | [unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-FP8](https://huggingface.co/unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-FP8) |
+| BF16 | [unsloth/NVIDIA-Nemotron-3-Super-120B-A12B](https://huggingface.co/unsloth/NVIDIA-Nemotron-3-Super-120B-A12B) |
+
+## Sources
+
+- Unsloth NVIDIA Nemotron 3 Super Documentation (How to Run)
+- GGUF: <https://huggingface.co/unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-GGUF>
\ No newline at end of file