Run antirez/deepseek-v4-gguf locally
antirez/deepseek-v4-gguf is a very large language model with 284.33 billion parameters, built on the deepseek4 architecture. It is released under the mit license and has been downloaded 6,434,367 times.
To run antirez/deepseek-v4-gguf locally at a 4,096-token context, its quantized versions need between 1027.81 GB (IQ2, lowest quality) and 1239.64 GB (Q4, highest quality) of memory, weights plus KV cache and a system margin included.
All quantizations
| Quant. | Bits | Quality | Weights | KV | Total | Speed~ | Verdict |
|---|---|---|---|---|---|---|---|
| IQ2 | 31.03 | Excellent | 1026.96 GB | 0.04 GB | 1027.81 GB | — | Insufficient |
| Q4 | 37.42 | Excellent | 1238.8 GB | 0.04 GB | 1239.64 GB | — | Insufficient |
KV cache computed from the model's exact architecture. Speed is a rough estimate bounded by memory bandwidth.
Frequently asked questions
Can I run antirez/deepseek-v4-gguf on an 8 GB GPU?
No. antirez/deepseek-v4-gguf does not fit on an 8 GB GPU, even with the smallest quantization and system RAM offloading.
Can I run antirez/deepseek-v4-gguf on a 16 GB GPU?
No. antirez/deepseek-v4-gguf does not fit on a 16 GB GPU, even with the smallest quantization and system RAM offloading.
Can I run antirez/deepseek-v4-gguf on a 24 GB GPU?
No. antirez/deepseek-v4-gguf does not fit on a 24 GB GPU, even with the smallest quantization and system RAM offloading.
What is the best quantization for antirez/deepseek-v4-gguf?
If memory allows, higher bits-per-weight means better quality. A common sweet spot is a Q4_K_M or Q5_K_M quantization, which keeps most of the quality while roughly halving the memory versus 8-bit. Pick the highest quantization that still fits in your VRAM.