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+---
+created: '2026-04-09T18:05:28+00:00'
+id: 4aec42e4-21ba-4279-b41b-58a8ebfefd73
+keywords:
+- Nemotron 3
+- NVIDIA
+- Nano-4B
+- Nano-30B-A3B
+- temperature
+- top_p
+- min_p
+- GGUF
+- quantization
+- UD-Q4_K_XL
+- Q8_0
+- NoPE
+- 1M context
+- llama.cpp
+- llama-server
+- MoE
+- tool calling
+- reasoning tokens
+links: []
+modified: '2026-04-09T18:05:28+00:00'
+summary: Optimal running parameters for NVIDIA's Nemotron 3 Nano family (4B and 30B-A3B),
+  covering inference settings for general chat vs tool calling, hardware requirements,
+  NoPE context extension, reasoning token handling, and llama.cpp example commands.
+tags:
+- reference
+- nemotron-3
+- nvidia
+- llm
+- inference
+- llama-cpp
+- local-ai
+title: NVIDIA Nemotron 3 Nano — Optimal Running Parameters
+---
+
+# NVIDIA Nemotron 3 Nano — Optimal Running Parameters
+
+A reference for optimally running NVIDIA's Nemotron 3 Nano family of hybrid MoE models locally.
+
+## Model Variants
+
+| Variant | Architecture | Context | Best Fit |
+|---|---|---|---|
+| **Nano-4B** | MoE | Up to **1M tokens** | Lightweight coding, math, agentic tasks; fits 5GB devices |
+| **Nano-30B-A3B** | MoE (3B active) | Up to **1M tokens** | Best performing for size; fits 24GB devices |
+| Super-120B-A12B | MoE (12B active) | Up to **1M tokens** | High-end workstation / server (separate guide) |
+
+> All Nemotron 3 models support a **1M-token context window**.
+
+## Recommended Inference Parameters
+
+NVIDIA recommends two parameter profiles depending on use-case:
+
+### 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 (`<think)>` / `</think)>`) |
+| `--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)
+
+| Variant | 4-bit | 8-bit | Notes |
+|---|---|---|---|
+| **Nano-4B** | ~3 GB | ~5 GB | Fits virtually any device |
+| **Nano-30B-A3B** | ~24 GB | ~36 GB | Fits 24GB Mac / RTX device |
+
+> **Architecture note:** Some GGUF quants end up similar in size because the model architecture has dimensions not divisible by 128, so parts can't be quantized to lower bits.
+
+### Quantization Recommendations
+
+- **Nano-4B**: Use **Q8_0** (8-bit) for near full precision — only 5GB.
+- **Nano-30B-A3B**: Use **UD-Q4_K_XL** (Dynamic 4-bit) — fits 24GB devices.
+
+## 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** — that's why the default is 262,144. Increase gradually as your RAM/VRAM allows.
+
+### NoPE — No Positional Embeddings
+
+Because Nemotron 3 was trained with **NoPE** (No Positional Embeddings):
+- You only need to change `max_position_embeddings` to extend context.
+- **YaRN is NOT needed** for context extension.
+- The model doesn't use explicit positional embeddings.
+
+## Chat Template Format
+
+Nemotron 3 uses the standard 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` in llama.cpp to see these tokens.
+- Use `--verbose-prompt` to see `<think)>` since it's prepended to assistant responses.
+
+## Critical Notes
+
+- The model outputs a reasoning channel (`<think)>..._think)>`) before the final answer in most cases.
+- Increase `max_new_tokens` for deep reasoning or long-form generation as RAM/VRAM allows.
+- For fine-tuning: use at least **75% reasoning** and **25% non-reasoning** data to retain reasoning capabilities.
+- The router layer is disabled by default in Unsloth fine-tuning for MoE models.
+
+## Example llama.cpp Commands
+
+### Nano-4B — General Instruction
+
+```bash
+./llama.cpp/llama-cli \
+    -hf unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF:Q8_0 \
+    --ctx-size 16384 \
+    --temp 1.0 --top-p 1.0
+```
+
+### Nano-4B — Tool Calling
+
+```bash
+./llama.cpp/llama-cli \
+    -hf unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF:Q8_0 \
+    --ctx-size 32768 \
+    --temp 0.6 --top-p 0.95
+```
+
+### Nano-4B — Conversation Mode (Local GGUF)
+
+```bash
+./llama.cpp/llama-cli \
+    --model unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF/NVIDIA-Nemotron-3-Nano-4B-Q8_0.gguf \
+    --ctx-size 16384 \
+    --seed 3407 \
+    --prio 2 \
+    --temp 0.6 \
+    --top-p 0.95
+```
+
+### Nano-30B-A3B — General Instruction
+
+```bash
+./llama.cpp/llama-cli \
+    -hf unsloth/Nemotron-3-Nano-30B-A3B-GGUF:UD-Q4_K_XL \
+    --ctx-size 32768 \
+    --temp 1.0 --top-p 1.0
+```
+
+### Nano-30B-A3B — Tool Calling
+
+```bash
+./llama.cpp/llama-cli \
+    -hf unsloth/Nemotron-3-Nano-30B-A3B-GGUF:UD-Q4_K_XL \
+    --ctx-size 32768 \
+    --temp 0.6 --top-p 0.95
+```
+
+### Nano-30B-A3B — Conversation Mode (Local GGUF)
+
+```bash
+./llama.cpp/llama-cli \
+    --model unsloth/Nemotron-3-Nano-30B-A3B-GGUF/Nemotron-3-Nano-30B-A3B-UD-Q4_K_XL.gguf \
+    --ctx-size 16384 \
+    --seed 3407 \
+    --prio 2 \
+    --temp 0.6 \
+    --top-p 0.95
+```
+
+### llama-server Deployment (Nano-30B-A3B)
+
+```bash
+./llama.cpp/llama-server \
+    --model unsloth/Nemotron-3-Nano-30B-A3B-GGUF/Nemotron-3-Nano-30B-A3B-UD-Q4_K_XL.gguf \
+    --alias "unsloth/Nemotron-3-Nano-30B-A3B" \
+    --prio 3 \
+    --min_p 0.01 \
+    --temp 0.6 --top-p 0.95 \
+    --ctx-size 16384 \
+    --port 8001
+```
+
+### OpenAI-Compatible Client
+
+After deploying via `llama-server`:
+
+```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/Nemotron-3-Nano-30B-A3B",
+    messages = [{"role": "user", "content": "What is 2+2?"}],
+)
+
+print(completion.choices[0].message.content)
+```
+
+## Sources
+
+- Unsloth NVIDIA Nemotron 3 Nano Documentation (How to Run)
+- GGUF collections:
+  - <https://huggingface.co/unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF>
+  - <https://huggingface.co/unsloth/Nemotron-3-Nano-30B-A3B-GGUF>
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