Moonlight 16B A3B Instruct GGUF — Hardware Requirements & GPU Compatibility
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515 downloads
12 likesSpecifications
- Publisher
- mmnga
- Family
- Moonlight
- Parameters
- 16B
- License
- MIT
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HuggingFace
How Much VRAM Does Moonlight 16B A3B Instruct GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 35.2 GB | — | 32.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Moonlight 16B A3B Instruct GGUF?
BF16 · 35.2 GBMoonlight 16B A3B Instruct GGUF (BF16) requires 35.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 46+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Moonlight 16B A3B Instruct GGUF?
BF16 · 35.2 GB13 devices with unified memory can run Moonlight 16B A3B Instruct GGUF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (36 GB).
Runs great
— Plenty of headroom
Related Models
Frequently Asked Questions
- How much VRAM does Moonlight 16B A3B Instruct GGUF need?
Moonlight 16B A3B Instruct GGUF requires 35.2 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 16B × 16 bits ÷ 8 = 32 GB
KV Cache + Overhead ≈ 3.2 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF1635.2 GB- Can NVIDIA GeForce RTX 5090 run Moonlight 16B A3B Instruct GGUF?
No — Moonlight 16B A3B Instruct GGUF requires at least 35.2 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Moonlight 16B A3B Instruct GGUF on a Mac?
Moonlight 16B A3B Instruct GGUF requires at least 35.2 GB at BF16, 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 Moonlight 16B A3B Instruct GGUF locally?
Yes — Moonlight 16B A3B Instruct GGUF can run locally on consumer hardware. At BF16 quantization it needs 35.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Moonlight 16B A3B Instruct GGUF?
At BF16, Moonlight 16B A3B Instruct GGUF can reach ~83 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 35.2 × 0.55 = ~83 tok/s
Estimated speed at BF16 (35.2 GB)
AMD Instinct MI300X~83 tok/sNVIDIA H100 SXM~62 tok/sAMD Instinct MI250X~51 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Moonlight 16B A3B Instruct GGUF?
At BF16, the download is about 32.00 GB.
- Which GPUs can run Moonlight 16B A3B Instruct GGUF?
No single consumer GPU has enough VRAM to run Moonlight 16B A3B Instruct GGUF at BF16 (35.2 GB). Multi-GPU or professional hardware is required.
- Which devices can run Moonlight 16B A3B Instruct GGUF?
13 devices with unified memory can run Moonlight 16B A3B Instruct GGUF at BF16 (35.2 GB), including Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.