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alt.freeweights.deepseek / deepseek-ai_DeepSeek-V3-0324-GGUF
From: bartowski <huggingface.co/bartowski>Newsgroups: alt.freeweights.deepseekSubject:

deepseek-ai_DeepSeek-V3-0324-GGUF

Date: 2026-11-15Commit: 338a226Signed: 2DC28CC7B26A283B ✓

Text generation model. Gguf weights, 8.29 TB in all. Published by bartowski under MIT.

deepseek8.29TBdeepseek-ai_DeepSeek-V3-0324-GGUFggufpermissive
FactsParamsnot statedSize8.29 TBFormatsggufTasktext generationLicenseMITFrom sourcepermissive
$ fw get bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF
# manifest sha256 315e05b51150… · 8.29 TB · 229 files
$ fw verify ./deepseek-ai_DeepSeek-V3-0324-GGUF bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF
From sourceHosted (signed)bartowski/deepseek-ai_DeepSeek-V3-0324-GGUFLast check: 2026-11-15 05:03 UTC
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Quantized of DeepSeek-V3-0324.

Works with

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Overview

Size
8.29 TB
Weights
134 GB (smallest of 26 GGUF variants)
Parameters
not stated
Formats
gguf
Task
text generation
License
MIT (permissive)
Files
229, each with a sha256
Publisher
bartowski
Added
2026-11-15
Section
alt.freeweights.deepseek
Lineage

Original release from the publisher.

Base model: deepseek-ai/DeepSeek-V3-0324

Where these bytes come from
Publisher at the pinned commit→You

Sources are tried in order. A file counts only when its size and sha256 match the manifest. Sources are checked when you ask for them, not on a timer.

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From sourcehuggingface.co2026-11-15 05:03 UTCpassed

Model card

From the publisher at commit 338a226. Shown as plain text with links; images open at the publisher.

Llamacpp imatrix Quantizations of DeepSeek-V3-0324 by deepseek-ai#

Using llama.cpp release b4944 for quantization.

Original model: https://huggingface.co/deepseek-ai/DeepSeek-V3-0324

All quants made using imatrix option with dataset from here

Run them in LM Studio

Run them directly with llama.cpp, or any other llama.cpp based project

Prompt format#

<｜begin▁of▁sentence｜>{system_prompt}<｜User｜>{prompt}<｜Assistant｜><｜end▁of▁sentence｜><｜Assistant｜>

V2 uploads#

I finally decided to go through llama-quant.cpp and update some of the tensor types, especially for MoE models, since they've kind of been left as-is since the original Mixtral.

These changes overall apply a bit more logic to the types, bumping a few values here and there across the board. These changes seem to have an overall positive impact on the results. They're similar to what Unsloth accomplished but they're in a more generic (and hopefully upstreamable) way.

The V2 weights uploaded are now final, I will delete the old ones if/when my PR is merged: https://github.com/ggml-org/llama.cpp/pull/12727

Download a file (not the whole branch) from below:#

FilenameQuant typeFile SizeSplitDescription
DeepSeek-V3-0324-Q8_0.ggufQ8_0713.29GBtrueExtremely high quality, generally unneeded but max available quant.
DeepSeek-V3-0324-Q6_K.ggufQ6_K550.80GBtrueVery high quality, near perfect, recommended.
DeepSeek-V3-0324-Q5_K_M.ggufQ5_K_M475.40GBtrueHigh quality, recommended.
DeepSeek-V3-0324-Q5_K_S.ggufQ5_K_S461.81GBtrueHigh quality, recommended.
DeepSeek-V3-0324-Q4_1.ggufQ4_1419.94GBtrueLegacy format, similar performance to Q4_K_S but with improved tokens/watt on Apple silicon.
DeepSeek-V3-0324-Q4_K_M-V2.ggufQ4_K_M406.99GBtrueAttempted to modify tensor quant levels for better performance. recommended
DeepSeek-V3-0324-Q4_K_M.ggufQ4_K_M404.43GBtrueGood quality, default size for most use cases, recommended.
DeepSeek-V3-0324-Q4_K_S.ggufQ4_K_S380.00GBtrueSlightly lower quality with more space savings, recommended.
DeepSeek-V3-0324-Q4_0.ggufQ4_0379.03GBtrueLegacy format, offers online repacking for ARM and AVX CPU inference.
DeepSeek-V3-0324-IQ4_NL.ggufIQ4_NL378.07GBtrueSimilar to IQ4_XS, but slightly larger. Offers online repacking for ARM CPU inference.
DeepSeek-V3-0324-IQ4_XS.ggufIQ4_XS357.13GBtrueDecent quality, smaller than Q4_K_S with similar performance, recommended.
DeepSeek-V3-0324-Q3_K_XL.ggufQ3_K_XL348.26GBtrueUses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability.
DeepSeek-V3-0324-Q3_K_M.ggufQ3_K_M319.20GBtrueLow quality.
DeepSeek-V3-0324-IQ3_XXS-V2.ggufIQ3_XXS261.74GBtrueAttempted to modify tensor quant levels for better performance.
DeepSeek-V3-0324-IQ3_XXS.ggufIQ3_XXS257.93GBtrueLower quality, new method with decent performance, comparable to Q3 quants.
DeepSeek-V3-0324-Q2_K_L-V2.ggufQ2_K_L247.35GBtrueAttempted to modify tensor quant levels for better performance. Also uses Q8_0 for embed and output weights.
DeepSeek-V3-0324-Q2_K_L.ggufQ2_K_L244.93GBtrueUses Q8_0 for embed and output weights. Very low quality but surprisingly usable.
DeepSeek-V3-0324-IQ2_M-V2.ggufIQ2_M224.49GBtrueAttempted to modify tensor quant levels for better performance.
DeepSeek-V3-0324-IQ2_M.ggufIQ2_M217.43GBtrueRelatively low quality, uses SOTA techniques to be surprisingly usable.
DeepSeek-V3-0324-IQ2_S.ggufIQ2_S197.00GBtrueLow quality, uses SOTA techniques to be usable.
DeepSeek-V3-0324-IQ2_XXS-V2.ggufIQ2_XXS188.95GBtrueAttempted to modify tensor quant levels for better performance.
DeepSeek-V3-0324-IQ2_XXS.ggufIQ2_XXS174.43GBtrueVery low quality, uses SOTA techniques to be usable.
DeepSeek-V3-0324-IQ1_M-V2.ggufIQ1_M154.78GBtrueAttempted to modify tensor quant levels for better performance. Extremely low quality, not recommended.
DeepSeek-V3-0324-IQ1_M.ggufIQ1_M148.88GBtrueExtremely low quality, not recommended.
DeepSeek-V3-0324-IQ1_S.ggufIQ1_S133.56GBtrueExtremely low quality, not recommended.

Embed/output weights#

Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to.

Downloading using huggingface-cli#

Click to view download instructions

First, make sure you have hugginface-cli installed:

pip install -U "huggingface_hub[cli]"

Then, you can target the specific file you want:

huggingface-cli download bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF --include "deepseek-ai_DeepSeek-V3-0324-Q4_K_M.gguf" --local-dir ./

If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:

huggingface-cli download bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF --include "deepseek-ai_DeepSeek-V3-0324-Q8_0/*" --local-dir ./

You can either specify a new local-dir (deepseek-ai_DeepSeek-V3-0324-Q8_0) or download them all in place (./)

ARM/AVX information#

Previously, you would download Q4_0_4_4/4_8/8_8, and these would have their weights interleaved in memory in order to improve performance on ARM and AVX machines by loading up more data in one pass.

Now, however, there is something called "online repacking" for weights. details in this PR. If you use Q4_0 and your hardware would benefit from repacking weights, it will do it automatically on the fly.

As of llama.cpp build b4282 you will not be able to run the Q4_0_X_X files and will instead need to use Q4_0.

Additionally, if you want to get slightly better quality for , you can use IQ4_NL thanks to this PR which will also repack the weights for ARM, though only the 4_4 for now. The loading time may be slower but it will result in an overall speed incrase.

Click to view Q4_0_X_X information (deprecated

I'm keeping this section to show the potential theoretical uplift in performance from using the Q4_0 with online repacking.

Click to view benchmarks on an AVX2 system (EPYC7702)

modelsizeparamsbackendthreadstestt/s% (vs Q4_0)
qwen2 3B Q4_01.70 GiB3.09 BCPU64pp512204.03 ± 1.03100%
qwen2 3B Q4_01.70 GiB3.09 BCPU64pp1024282.92 ± 0.19100%
qwen2 3B Q4_01.70 GiB3.09 BCPU64pp2048259.49 ± 0.44100%
qwen2 3B Q4_01.70 GiB3.09 BCPU64tg12839.12 ± 0.27100%
qwen2 3B Q4_01.70 GiB3.09 BCPU64tg25639.31 ± 0.69100%
qwen2 3B Q4_01.70 GiB3.09 BCPU64tg51240.52 ± 0.03100%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64pp512301.02 ± 1.74147%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64pp1024287.23 ± 0.20101%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64pp2048262.77 ± 1.81101%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64tg12818.80 ± 0.9948%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64tg25624.46 ± 3.0483%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64tg51236.32 ± 3.5990%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64pp512271.71 ± 3.53133%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64pp1024279.86 ± 45.63100%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64pp2048320.77 ± 5.00124%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64tg12843.51 ± 0.05111%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64tg25643.35 ± 0.09110%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64tg51242.60 ± 0.31105%

Q4_0_8_8 offers a nice bump to prompt processing and a small bump to text generation

Which file should I choose?#

Click here for details

A great write up with charts showing various performances is provided by Artefact2 here

The first thing to figure out is how big a model you can run. To do this, you'll need to figure out how much RAM and/or VRAM you have.

If you want your model running as FAST as possible, you'll want to fit the whole thing on your GPU's VRAM. Aim for a quant with a file size 1-2GB smaller than your GPU's total VRAM.

If you want the absolute maximum quality, add both your system RAM and your GPU's VRAM together, then similarly grab a quant with a file size 1-2GB Smaller than that total.

Next, you'll need to decide if you want to use an 'I-quant' or a 'K-quant'.

If you don't want to think too much, grab one of the K-quants. These are in format 'QX_K_X', like Q5_K_M.

If you want to get more into the weeds, you can check out this extremely useful feature chart:

llama.cpp feature matrix

But basically, if you're aiming for below Q4, and you're running cuBLAS (Nvidia) or rocBLAS (AMD), you should look towards the I-quants. These are in format IQX_X, like IQ3_M. These are newer and offer better performance for their size.

These I-quants can also be used on CPU, but will be slower than their K-quant equivalent, so speed vs performance is a tradeoff you'll have to decide.

Credits#

Thank you kalomaze and Dampf for assistance in creating the imatrix calibration dataset.

Thank you ZeroWw for the inspiration to experiment with embed/output.

Thank you to LM Studio for sponsoring my work.

Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski

Files

229 files · 8.29 TBWeights 134 GB (smallest of 26 GGUF variants). Sizes and sha256 from the signed manifest.
Show all 229 files with their sha256
FileSizesha256
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README.md14.8 KBb6d104acfd8b02eb1dcc82e120db6641e85ca20cf2e7dbc14a6b3f6510ca7671
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deepseek-ai_DeepSeek-V3-0324-Q6_K/deepseek-ai_DeepSeek-V3-0324-Q6_K-00015-of-00015.gguf22.0 GBf1bfacc2a6cf61a7c48355c878e44a77b3e22689256adb3b3419f17ff46fd829
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00001-of-00020.gguf36.5 GBe4e594d7d24773ca618d0fa5b05bcf008cdd604be6d684f1209bf3c1f90f6970
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00002-of-00020.gguf36.7 GB9c8fcb7118434aede3da5870bd195d8d16fc583d0611a30b39cf3153d91da5f8
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00003-of-00020.gguf36.7 GB5a2e2a971f4989b145093ebe58d050dd9790ac100119b3d185ded0c98a97d61d
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00004-of-00020.gguf36.7 GB5e880ff82f6a4ad3556b9900a3a683f77bedbe9c3d7f5463ae665bc9d1c60f24
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00005-of-00020.gguf36.7 GB407af715d0b711c022002680d6c6a633b070a72b24e425b02f1ed7c283a19ba5
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00006-of-00020.gguf36.7 GBee9a10f0f1798a374a3860c217656f53dfaf60d69774322c77c4170b78c97b0b
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00007-of-00020.gguf36.7 GB3d54587978dbc59131c0e174a3549b6ca0b7a6cf8a88284fba2c92b26c4771f4
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00008-of-00020.gguf36.7 GB49403765557786181065fe9cb94a5d52e9635876c352170f6c9090b531770c50
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00009-of-00020.gguf36.7 GB42cea9d451f9b567c0643af296e55d309a9a0a6538f8bdc713877598254ce04f
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00010-of-00020.gguf36.7 GB3b999f22ac898b5d7fcb6753e281f12365890abfcf7e24228d6a881ba6051dba
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00011-of-00020.gguf36.7 GB23832febb744f6a76f91b52b689cacd6e13a1e830ee66998511e76578aff09e3
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00012-of-00020.gguf36.7 GBb13115875786ff3db4e842a4215498e7f99b139b9d611ec65f0e12591a228efe
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00013-of-00020.gguf36.7 GB879a41212a56182a0e20feb70f9cd6ae68065cbaa41867297509ce24aeac2913
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00014-of-00020.gguf36.7 GB3508bd43dc17989d1517bf76f5386f153395a7e5c90afb9ecd5cb4addac345eb
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00015-of-00020.gguf36.7 GB7a3150792797b130cf55f1aea561a3ff39146ed3287ed6cd711a7bf54d2af7d4
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00016-of-00020.gguf36.7 GB2ecf243e3b6938c19ce04f5d28a20213d09347262318b8bafe769e631fce6945
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00017-of-00020.gguf36.7 GBf192c84055b865dde4f58c6fa687c3a1e4549165a153005a60d6d5d8e41cc257
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00018-of-00020.gguf36.7 GB538cd02ca07b3db6828cf3a6e87e04726eea782f898d36ccc9dcd32a7d45d9a3
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00019-of-00020.gguf36.7 GB21e313bedccf71dc9573262a1a20a7c1789dd7315eb2cb7230b4e9c208081d3b
deepseek-ai_DeepSeek-V3-0324-Q8_0/deepseek-ai_DeepSeek-V3-0324-Q8_0-00020-of-00020.gguf16.2 GB6f85b383816b44d8bfde696117a2bd62ed74150cdb88571e200c14e5b2a7e5b9
deepseek-ai_DeepSeek-V3-0324.imatrix987 MB6405be49fd270b5b38d768d02d4288bd9ebef1025b0b69cea810f742f5f8c721
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
338a2262ac pinned now2026-11-15 05:03 UTC229 files · 8.29 TB

Use it

$ fw get bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF
# manifest sha256 315e05b51150… · 8.29 TB · 229 files
$ fw verify ./deepseek-ai_DeepSeek-V3-0324-GGUF bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF.json --dir ./deepseek-ai_DeepSeek-V3-0324-GGUF $ python3 fw.py verify ./deepseek-ai_DeepSeek-V3-0324-GGUF ./bartowski__deepseek-ai_DeepSeek-V3-0324-GGUF.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF --revision 338a2262ace212c74ba4e1456890ee0bd2b7ab90 --local-dir ./deepseek-ai_DeepSeek-V3-0324-GGUF
llama.cppDownload one GGUF variant (deepseek-ai_DeepSeek-V3-0324-IQ1_S, 134 GB), then serve it.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF --include "deepseek-ai_DeepSeek-V3-0324-IQ1_S/*" --local-dir ./deepseek-ai_DeepSeek-V3-0324-GGUF $ llama-server -m ./deepseek-ai_DeepSeek-V3-0324-GGUF/deepseek-ai_DeepSeek-V3-0324-IQ1_S/deepseek-ai_DeepSeek-V3-0324-IQ1_S-00001-of-00004.gguf
OllamaMake an Ollama model from the downloaded file.
$ printf 'FROM ./deepseek-ai_DeepSeek-V3-0324-GGUF/deepseek-ai_DeepSeek-V3-0324-IQ1_S/deepseek-ai_DeepSeek-V3-0324-IQ1_S-00001-of-00004.gguf\n' > Modelfile $ ollama create deepseek-ai-deepseek-v3-0324-gguf -f Modelfile

License

Name
MIT License
Id
MIT
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
License as declared by the publisher. No person read it. 2026-11-15
Text in
README.md
Text sha256
b6d104acfd8b02eb1dcc82e120db6641e85ca20cf2e7dbc14a6b3f6510ca7671
Terms gate
No extra terms beyond the license.

Read the license text

Licenses are checked against the license table. A custom license passes only after a person reads it.

Provenance

From: bartowski <huggingface.co/bartowski>Newsgroups: alt.freeweights.deepseekSubject: deepseek-ai_DeepSeek-V3-0324-GGUFDate: 2026-11-15Commit: 338a226Signed: 2DC28CC7B26A283B ✓
Upstream
bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF
Pinned commit
338a2262ace212c74ba4e1456890ee0bd2b7ab90
Manifest
deepseek-ai_DeepSeek-V3-0324-GGUF.json · .minisig
Manifest sha256
315e05b51150cc1e604c31cb507f74ae0f5fae4286d352dffd227a4b2cdab348
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 05:03 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF.json $ curl -O https://freeweights.allternit.com/manifests/bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF.json.minisig $ minisign -Vm deepseek-ai_DeepSeek-V3-0324-GGUF.json -P RWQ7KGqyx4zCLXtUFOqvfv8L3g+8fpKJ1FsuxPyOYMF+4KufbUxKq1Oq $ shasum -a 256 <file> # compare with the Files tab

A manifest whose signature fails must be rejected. A file whose size or sha256 does not match must be discarded. Verify a download

Model tree

Parent

deepseek-ai/DeepSeek-V3-0324 · this model is a quantization of it

No model in the catalog names this one as its parent.

Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF
Open in Freeweights Studio

Pull, verify and run it in the Allternit app on Desktop, web or phone.

Signed manifest
minisign, key 2DC28CC7B26A283B. deepseek-ai_DeepSeek-V3-0324-GGUF.json. Provenance. Takedown history: none.
Source
huggingface.co/bartowski/deepseek-ai_DeepSeek-V3-0324-GGUF

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