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deepseek-ai

DeepSeek-V4-Pro-0813

Parameters
1,573B
Max context length
1,048,576
Architecture
deepseek4
License
Commercial OK
Base model
deepseek-ai/DeepSeek-V4-Pro-0813
License
mit
llama.cpp
b9840+

About DeepSeek-V4-Pro-0813

DeepSeek-V4-Pro-0813 is a GGUF model based on deepseek-ai/DeepSeek-V4-Pro-0813 on Hugging Face. GGUF files are published by unsloth/DeepSeek-V4-Pro-0813-GGUF. It has about 1,573B parameters, the deepseek4 architecture, a maximum context length of 1,048,576 tokens (values written in the GGUF).

There are 2 quantizations, with file sizes from 850 GB (UD-Q4_K_XL) to 873 GB (UD-Q8_K_XL) (actual sizes on Hugging Face).

Running UD-Q4_K_XL (850 GB) with an 8,192-token context needs an estimated 851 GB of memory, and an estimated 851 GB at 32,768 tokens.

The original model is licensed under MIT License, which allows commercial use (keep the license text and copyright notice when redistributing). Check the original license for the terms of use.

File size and estimated memory per quantization

  • Up to 8 GB
  • Up to 16 GB
  • Up to 24 GB
  • Up to 48 GB
  • Up to 128 GB
  • More

File sizes are the actual values on Hugging Face. Memory is estimated for each context length (KV cache f16). The formula is in How memory is calculated.

All memory figures are Estimated (KV cache f16). It should run on a setup with at least this much VRAM (or Mac unified memory). Click a value to see the devices and models that fit that amount (Find by GPU / Mac).

About the "quality guide" (how far a quantization drifts from the original)

For each quantization type, how far the output drifts from the original model, grouped into six levels from values llama.cpp measured on Llama-3-8B.

The value is mean KLD (the difference between the original and quantized model in next-token probabilities); smaller means closer to the original. Quantizations made with an imatrix (importance data) come out slightly smaller. Levels use the value without an imatrix (or with one, for types that only have that).

These values were not measured on this model. Larger models and MoE models tend to drift less with the same type. Distributor-specific mixed types (such as UD-Q4_K_XL) cannot be matched by type name alone, so they show "-".

Quantization Quality guide KLD (no imatrix) KLD (imatrix) Size (Llama-3-8B)
Q8_0 Nearly identical 0.0014 - 7.96 GiB
Q6_K Very small 0.0055 - 6.14 GiB
Q5_K_M Very small 0.0108 - 5.33 GiB
Q5_K_S Small 0.0166 - 5.21 GiB
Q5_1 Small 0.0180 - 5.65 GiB
Q5_0 Small 0.0222 - 5.21 GiB
Q4_K_M Small 0.0313 0.0282 4.58 GiB
Q4_K_S Medium 0.0431 0.0320 4.37 GiB
IQ4_NL Small - 0.0357 4.35 GiB
IQ4_XS Small - 0.0363 4.14 GiB
Q4_1 Medium 0.0717 - 4.78 GiB
Q4_0 Medium 0.0719 - 4.34 GiB
Q3_K_L Medium 0.0872 0.0731 4.03 GiB
Q3_K_M Medium 0.1019 0.0844 3.74 GiB
IQ3_M Medium - 0.1025 3.53 GiB
IQ3_S Medium - 0.1113 3.42 GiB
IQ3_XS Large - 0.1387 3.28 GiB
IQ3_XXS Large - 0.1836 3.05 GiB
Q3_K_S Large 0.2282 0.1998 3.41 GiB
IQ2_M Large - 0.3260 2.74 GiB
Q2_K Very large 0.4451 0.3322 2.96 GiB
Q2_K_S Very large - 0.4034 2.96 GiB
IQ2_S Very large - 0.4392 2.56 GiB
IQ2_XS Very large - 0.5463 2.43 GiB
IQ2_XXS Very large - 0.8120 2.24 GiB
IQ1_M Very large - 1.3931 2.01 GiB
IQ1_S Very large - 2.2546 1.88 GiB

Source: llama.cpp (MIT), measured on Llama-3-8B against FP16, Wikitext-2, revision f364eb6f. Original table · Reading and choosing quantizations

GGUF source

unsloth/DeepSeek-V4-Pro-0813-GGUF

Converted and published by a third party About this label

Last checked: Nov 11, 2026

Architecture
deepseek4
llama.cpp b9840 and later
Parameters
1,573.0B
Max context length
1,048,576
License
mit Commercial OK
File size and memory per quantization for DeepSeek-V4-Pro-0813 (unsloth/DeepSeek-V4-Pro-0813-GGUF)
Quantization File size Measured Quality guide 4,096 8,192 16,384 32,768 65,536 131,072 262,144 1,048,576 max
UD-Q4_K_XL (20 parts) 850 GB - 851 GB 851 GB 851 GB 851 GB 851 GB 852 GB 853 GB 861 GB
UD-Q8_K_XL (20 parts) 873 GB - 874 GB 874 GB 874 GB 875 GB 875 GB 876 GB 877 GB 885 GB 
Ollama  ollama run hf.co/unsloth/DeepSeek-V4-Pro-0813-GGUF:UD-Q4_K_XL
llama.cpp  llama-server -hf unsloth/DeepSeek-V4-Pro-0813-GGUF:UD-Q4_K_XL

Third-party evaluations

Values from other organizations for the original model before quantization. Not this site's own rating. Values are for the original model before quantization. GGUF quantization (especially small quantizations) can lower performance.

Capabilities (Epoch AI)

155.9 154.0–158.0

DeepSeek V4 Pro 0813 · Values as of Aug 13, 2026

Source: Epoch Capabilities Index (Epoch AI) (CC BY 4.0). Original leaderboard · See in ranking

License and commercial use

MIT License Commercial OK

Allows commercial use, modification and redistribution. When redistributing, keep the copyright notice and license text.

Based on the license on the original model's Hugging Face page. Original license text (checked Oct 18, 2026)

The summary states facts this site read from the original text and is not legal advice. Always check the original license and its latest terms before use. All licenses

How to run

Mainline llama.cpp can load this model's format (deepseek4) from b9840 (Jun 29, 2026) onward. Ollama and LM Studio bundle llama.cpp internally, so an older app fails to load it with errors such as "unknown model architecture". If that happens, update the app.

Example commands using UD-Q4_K_XL. To use another quantization, replace the name with one from the table above. How to run local LLMs

Ollama

Run it by pointing directly at the GGUF on Hugging Face.

ollama run hf.co/unsloth/DeepSeek-V4-Pro-0813-GGUF:UD-Q4_K_XL

llama.cpp

Pass the repository and quantization name to llama-server (or llama-cli) with -hf.

llama-server -hf unsloth/DeepSeek-V4-Pro-0813-GGUF:UD-Q4_K_XL

LM Studio

Paste unsloth/DeepSeek-V4-Pro-0813-GGUF into the search box, download it, and choose the quantization from the file list.

Frequently asked questions

How much memory do I need to run DeepSeek-V4-Pro-0813 (UD-Q4_K_XL)?
The file size is 850 GB (measured). With a 8,192-token context, the estimated memory including the KV cache is 851 GB. The formula is published at https://localllm.az-arte.com/en/guide/memory-calculation.
Can DeepSeek-V4-Pro-0813 be used commercially?
The original model's license is MIT License (Commercial use allowed).Allows commercial use, modification and redistribution. When redistributing, keep the copyright notice and license text. Check the original license text before deciding.
Does DeepSeek-V4-Pro-0813 run in 8 GB, 12 GB, 16 GB or 24 GB of VRAM?
8 GB: no quantization fits; 12 GB: no quantization fits; 16 GB: no quantization fits; 24 GB: no quantization fits (estimated at 8,192 tokens with an f16 KV cache, files from the most-downloaded source).
What is the command to run DeepSeek-V4-Pro-0813 with Ollama?
Run "ollama run hf.co/unsloth/DeepSeek-V4-Pro-0813-GGUF:UD-Q4_K_XL" to use the GGUF on Hugging Face directly. To use another quantization, replace the name at the end.