Nemotron Content Safety Reasoning 4B — Hardware Requirements & GPU Compatibility
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Nemotron Content Safety Reasoning 4B is a 4.3B-parameter open language model from NVIDIA in the Nemotron family. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 3.24 GB of VRAM — see which GPUs and Macs can run it below.
2.3K downloads
19 likesSpecifications
- Publisher
- NVIDIA
- Family
- Nemotron
- Parameters
- 4.3B
- Architecture
- Gemma3ForConditionalGeneration
- Context Length
- 131,072 tokens
- Vocabulary Size
- 262,208
- Release Date
- 2025-11-26
- License
- Other
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HuggingFace
How Much VRAM Does Nemotron Content Safety Reasoning 4B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 2.5 GB | 24.9 GB | 1.83 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 2.8 GB | 25.2 GB | 2.10 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 3.2 GB | 25.7 GB | 2.58 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 3.7 GB | 26.2 GB | 3.06 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 4.2 GB | 26.7 GB | 3.55 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 5.0 GB | 27.4 GB | 4.30 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 9.3 GB | 31.7 GB | 8.60 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Nemotron Content Safety Reasoning 4B?
Q4_K_M · 3.2 GBNemotron Content Safety Reasoning 4B (Q4_K_M) requires 3.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 5+ GB is recommended. Using the full 131K context window can add up to 22.5 GB, bringing total usage to 25.7 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Nemotron Content Safety Reasoning 4B?
Q4_K_M · 3.2 GB59 devices with unified memory can run Nemotron Content Safety Reasoning 4B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Nemotron Content Safety Reasoning 4B need?
Nemotron Content Safety Reasoning 4B requires 3.2 GB of VRAM at Q4_K_M, or 9.3 GB at BF16. Full 131K context adds up to 22.5 GB (25.7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 4.3B × 4.8 bits ÷ 8 = 2.6 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 23.1 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M3.2 GBQ4_K_M + full context25.7 GB- What's the best quantization for Nemotron Content Safety Reasoning 4B?
For Nemotron Content Safety Reasoning 4B, Q4_K_M (3.2 GB) offers the best balance of quality and VRAM usage. Q5_K_M (3.7 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 2.5 GB.
VRAM requirement by quantization
Q2_K2.5 GBQ4_K_M ★3.2 GBQ5_K_M3.7 GBQ6_K4.2 GBQ8_05.0 GBBF169.3 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Nemotron Content Safety Reasoning 4B on a Mac?
Nemotron Content Safety Reasoning 4B requires at least 2.5 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Nemotron Content Safety Reasoning 4B locally?
Yes — Nemotron Content Safety Reasoning 4B can run locally on consumer hardware. At Q4_K_M quantization it needs 3.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Nemotron Content Safety Reasoning 4B?
At Q4_K_M, Nemotron Content Safety Reasoning 4B can reach ~1358 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~202 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 3.2 × 0.65 = ~1605 tok/s
Estimated speed at Q4_K_M (3.2 GB)
~1605 tok/s~202 tok/s~1605 tok/s~1358 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Nemotron Content Safety Reasoning 4B?
At Q4_K_M, the download is about 2.58 GB. The full-precision BF16 version is 8.60 GB. The smallest option (Q2_K) is 1.83 GB.
- Which GPUs can run Nemotron Content Safety Reasoning 4B?
50 consumer GPUs can run Nemotron Content Safety Reasoning 4B at Q4_K_M (3.2 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 50 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Nemotron Content Safety Reasoning 4B?
59 devices with unified memory can run Nemotron Content Safety Reasoning 4B at Q4_K_M (3.2 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.