DeepSeek-V4-Flash-0731 GGUF size and VRAM requirements
bartowski/DeepSeek-V4-Flash-0731-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 15,437 times.
To run bartowski/DeepSeek-V4-Flash-0731-GGUF locally at a 4,096-token context, its quantized versions need between 146.77 GB (GGUF, lowest quality) and 146.77 GB (GGUF, highest quality) of memory, weights plus KV cache and a system margin included.
Available GGUF quantizations for bartowski/DeepSeek-V4-Flash-0731-GGUF include GGUF. The model supports a native context length of up to 1,048,576 tokens; a longer context grows the KV cache and the memory needed.
GGUF file size and memory by quantization
Compare real GGUF weight sizes, estimated KV cache and total memory for Q4, Q5, Q8 and every quantization published in this repository.
| Quant. | Bits | Quality | Weights | KV | Total | Speed~ | Verdict |
|---|---|---|---|---|---|---|---|
| GGUF | 4.4 | Good | 145.64 GB | 0.34 GB | 146.77 GB | — | Insufficient |
KV cache computed from the model's exact architecture. Speed is a rough estimate bounded by memory bandwidth.
Frequently asked questions
What kind of model is bartowski/DeepSeek-V4-Flash-0731-GGUF?
bartowski/DeepSeek-V4-Flash-0731-GGUF is a language model with 284.33 billion parameters, based on the deepseek4 architecture. It is released under the mit license and distributed as GGUF files for local inference.
Can I run bartowski/DeepSeek-V4-Flash-0731-GGUF on an 8 GB GPU?
No. bartowski/DeepSeek-V4-Flash-0731-GGUF does not fit on an 8 GB GPU, even with the smallest quantization and system RAM offloading.
Can I run bartowski/DeepSeek-V4-Flash-0731-GGUF on a 16 GB GPU?
No. bartowski/DeepSeek-V4-Flash-0731-GGUF does not fit on a 16 GB GPU, even with the smallest quantization and system RAM offloading.
Can I run bartowski/DeepSeek-V4-Flash-0731-GGUF on a 24 GB GPU?
No. bartowski/DeepSeek-V4-Flash-0731-GGUF does not fit on a 24 GB GPU, even with the smallest quantization and system RAM offloading.
What context length does bartowski/DeepSeek-V4-Flash-0731-GGUF support?
bartowski/DeepSeek-V4-Flash-0731-GGUF supports a native context length of up to 1,048,576 tokens. A longer context grows the KV cache, so it increases the memory needed to run the model.
What is the best quantization for bartowski/DeepSeek-V4-Flash-0731-GGUF?
For bartowski/DeepSeek-V4-Flash-0731-GGUF, 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.