GPT Neox 20B Fiction Novel Generation Q4 K M GGUF — Hardware Requirements & GPU Compatibility
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GPT Neox 20B Fiction Novel Generation Q4 K M GGUF is a 20B-parameter open language model from ywms666. At Q4_K_M it needs about 13.20 GB of VRAM — see which GPUs and Macs can run it below.
28 downloads
1 likesSpecifications
- Publisher
- ywms666
- Parameters
- 20B
- License
- MIT
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How Much VRAM Does GPT Neox 20B Fiction Novel Generation Q4 K M GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q4_K_M | 4.80 | 13.2 GB | — | 12.00 GB | 4-bit medium quantization — most popular sweet spot |
Which GPUs Can Run GPT Neox 20B Fiction Novel Generation Q4 K M GGUF?
Q4_K_M · 13.2 GBGPT Neox 20B Fiction Novel Generation Q4 K M GGUF (Q4_K_M) requires 13.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 18+ GB is recommended. 17 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 5080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run GPT Neox 20B Fiction Novel Generation Q4 K M GGUF?
Q4_K_M · 13.2 GB27 devices with unified memory can run GPT Neox 20B Fiction Novel Generation Q4 K M GGUF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does GPT Neox 20B Fiction Novel Generation Q4 K M GGUF need?
GPT Neox 20B Fiction Novel Generation Q4 K M GGUF requires 13.2 GB of VRAM at Q4_K_M.
VRAM = Weights + KV Cache + Overhead
Weights = 20B × 4.8 bits ÷ 8 = 12 GB
KV Cache + Overhead ≈ 1.2 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M13.2 GB- Can I run GPT Neox 20B Fiction Novel Generation Q4 K M GGUF on a Mac?
GPT Neox 20B Fiction Novel Generation Q4 K M GGUF requires at least 13.2 GB at Q4_K_M, 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 GPT Neox 20B Fiction Novel Generation Q4 K M GGUF locally?
Yes — GPT Neox 20B Fiction Novel Generation Q4 K M GGUF can run locally on consumer hardware. At Q4_K_M quantization it needs 13.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is GPT Neox 20B Fiction Novel Generation Q4 K M GGUF?
At Q4_K_M, GPT Neox 20B Fiction Novel Generation Q4 K M GGUF can reach ~221 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~50 tok/s. 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 ÷ 13.2 × 0.55 = ~221 tok/s
Estimated speed at Q4_K_M (13.2 GB)
~221 tok/s~50 tok/s~165 tok/s~137 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of GPT Neox 20B Fiction Novel Generation Q4 K M GGUF?
At Q4_K_M, the download is about 12.00 GB.
- Which GPUs can run GPT Neox 20B Fiction Novel Generation Q4 K M GGUF?
17 consumer GPUs can run GPT Neox 20B Fiction Novel Generation Q4 K M GGUF at Q4_K_M (13.2 GB). Top options include AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090, AMD Radeon RX 6800. 6 GPUs have plenty of headroom for comfortable inference.
- Which devices can run GPT Neox 20B Fiction Novel Generation Q4 K M GGUF?
27 devices with unified memory can run GPT Neox 20B Fiction Novel Generation Q4 K M GGUF at Q4_K_M (13.2 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.