Nemotron Mini 4B Instruct — Hardware Requirements & GPU Compatibility
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Nemotron Mini 4B Instruct is a 4B-parameter open language model from NVIDIA in the Nemotron family. It supports a context window of up to 4,096 tokens. At Q4_K_M it needs about 2.97 GB of VRAM — see which GPUs and Macs can run it below.
473.9K downloads
182 likesSpecifications
- Publisher
- NVIDIA
- Family
- Nemotron
- Parameters
- 4B
- Architecture
- NemotronForCausalLM
- Context Length
- 4,096 tokens
- Vocabulary Size
- 256,000
- Release Date
- 2024-09-10
- License
- Other
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HuggingFace
How Much VRAM Does Nemotron Mini 4B Instruct Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 2.3 GB | 2.5 GB | 1.70 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 2.3 GB | 2.6 GB | 1.75 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 2.5 GB | 2.8 GB | 1.95 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 2.6 GB | 2.8 GB | 2.00 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 3.0 GB | 3.2 GB | 2.40 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 3.4 GB | 3.7 GB | 2.85 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 3.9 GB | 4.1 GB | 3.30 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 4.6 GB | 4.8 GB | 4.00 GB | 8-bit quantization, near-lossless |
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 Mini 4B Instruct?
Q4_K_M · 3.0 GBNemotron Mini 4B Instruct (Q4_K_M) requires 3.0 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 4+ GB is recommended. Using the full 4K context window can add up to 0.3 GB, bringing total usage to 3.2 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 Mini 4B Instruct?
Q4_K_M · 3.0 GB59 devices with unified memory can run Nemotron Mini 4B Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomWhere to Download Nemotron Mini 4B Instruct
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Related Models
Frequently Asked Questions
- How much VRAM does Nemotron Mini 4B Instruct need?
Nemotron Mini 4B Instruct requires 3.0 GB of VRAM at Q4_K_M, or 8.6 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 4B × 4.8 bits ÷ 8 = 2.4 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 0.8 GB (at full 4K context)
VRAM usage by quantization
Q4_K_M3.0 GBQ4_K_M + full context3.2 GB- What's the best quantization for Nemotron Mini 4B Instruct?
For Nemotron Mini 4B Instruct, Q4_K_M (3.0 GB) offers the best balance of quality and VRAM usage. Q4_K_L (3.0 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XS at 1.8 GB.
VRAM requirement by quantization
IQ2_XS1.8 GBQ3_K_M2.5 GBQ4_K_S2.8 GBQ4_K_M ★3.0 GBQ5_K_M3.4 GBBF168.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Nemotron Mini 4B Instruct on a Mac?
Nemotron Mini 4B Instruct requires at least 1.8 GB at IQ2_XS, 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 Mini 4B Instruct locally?
Yes — Nemotron Mini 4B Instruct can run locally on consumer hardware. At Q4_K_M quantization it needs 3.0 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Nemotron Mini 4B Instruct?
At Q4_K_M, Nemotron Mini 4B Instruct can reach ~1482 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~221 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 ÷ 3.0 × 0.65 = ~1751 tok/s
Estimated speed at Q4_K_M (3.0 GB)
~1751 tok/s~221 tok/s~1751 tok/s~1482 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Nemotron Mini 4B Instruct?
At Q4_K_M, the download is about 2.40 GB. The full-precision BF16 version is 8.00 GB. The smallest option (IQ2_XS) is 1.20 GB.
- Which GPUs can run Nemotron Mini 4B Instruct?
50 consumer GPUs can run Nemotron Mini 4B Instruct at Q4_K_M (3.0 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 Mini 4B Instruct?
59 devices with unified memory can run Nemotron Mini 4B Instruct at Q4_K_M (3.0 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.