alt.freeweights.mistral / Mixtral-8x22B-v0.1
From: mistralai <huggingface.co/mistralai>Newsgroups: alt.freeweights.mistralSubject:

Mixtral-8x22B-v0.1

Date: 2026-11-14Commit: e1cd34fSigned: 2DC28CC7B26A283B ✓

Model with 140.6B parameters. Safetensors weights, 281 GB in all. Published by mistralai under Apache-2.0.

140.6B params281GBMixtral-8x22B-v0.1safetensorspermissive
FactsParams140.6BSize281 GBFormatssafetensorsTasknot taggedLicenseApache-2.0From sourcepermissive
$ fw get mistralai/Mixtral-8x22B-v0.1
# manifest sha256 02eb2757ba83… · 281 GB · 69 files
$ fw verify ./Mixtral-8x22B-v0.1 mistralai/Mixtral-8x22B-v0.1
From sourceHosted (signed)mistralai/Mixtral-8x22B-v0.1Last check: 2026-11-14 21:24 UTC

Get help: custom fine-tune or private deploy. We review your setup before we quote.

Works with

Runs with

Ranked by fit to this model (safetensors), then by GitHub stars.

Overview

Size
281 GB
Weights
281 GB (safetensors)
Parameters
140.6B
Formats
safetensors
Task
not tagged
License
Apache-2.0 (permissive)
Files
69, each with a sha256
Publisher
mistralai
Added
2026-11-14
Section
alt.freeweights.mistral
Lineage

Original release from the publisher.

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.

Sources
BadgeHostLast checkResult
From sourcehuggingface.co2026-11-14 21:24 UTCpassed

Model card

From the publisher at commit e1cd34f. Shown as plain text with links; images open at the publisher.

Model Card for Mixtral-8x22B#

The Mixtral-8x22B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts.

For full details of this model please read our release blog post.

Warning#

This repo contains weights that are compatible with vLLM serving of the model as well as Hugging Face transformers library. It is based on the original Mixtral torrent release, but the file format and parameter names are different.

Run the model#

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "mistralai/Mixtral-8x22B-v0.1"
tokenizer = AutoTokenizer.from_pretrained(model_id)

model = AutoModelForCausalLM.from_pretrained(model_id)

text = "Hello my name is"
inputs = tokenizer(text, return_tensors="pt")

outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

By default, transformers will load the model in full precision. Therefore you might be interested to further reduce down the memory requirements to run the model through the optimizations we offer in HF ecosystem:

Notice#

Mixtral-8x22B is a pretrained base model and therefore does not have any moderation mechanisms.

The Mistral AI Team#

Albert Jiang, Alexandre Sablayrolles, Alexis Tacnet, Antoine Roux, Arthur Mensch, Audrey Herblin-Stoop, Baptiste Bout, Baudouin de Monicault, Blanche Savary, Bam4d, Caroline Feldman, Devendra Singh Chaplot, Diego de las Casas, Eleonore Arcelin, Emma Bou Hanna, Etienne Metzger, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Harizo Rajaona, Jean-Malo Delignon, Jia Li, Justus Murke, Louis Martin, Louis Ternon, Lucile Saulnier, Lélio Renard Lavaud, Margaret Jennings, Marie Pellat, Marie Torelli, Marie-Anne Lachaux, Nicolas Schuhl, Patrick von Platen, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Thibaut Lavril, Timothée Lacroix, Théophile Gervet, Thomas Wang, Valera Nemychnikova, William El Sayed, William Marshall

Files

69 files · 281 GBWeights 281 GB (safetensors). Sizes and sha256 from the signed manifest.
Show all 69 files with their sha256
FileSizesha256
.gitattributes1.57 KBeb86bb68ee5c7648b03ab5b116ef46a574f57d63836a4a8137da45572801a63b
README.md2.45 KB46fd106487e7081f035c5e1caed05f6a4df16689b4e901aa5d79e3b325b40e80
config.json714 B289373ddfa7e553901931368a57ddf21b0065662cbaf7591e14f486d828e628e
generation_config.json111 Bd90538450467bfd74379882931354f442370a98602d55f215039d59aa78570b7
model-00001-of-00059.safetensors5.00 GB111cce2f7d94e90d2c4d82061ab9e91fbc4355b4217fb3065ae01ca4fa7ba523
model-00002-of-00059.safetensors4.81 GBd836890a32de1597279722d666d45104eacb3a114b42fdaf01bcaf4ada0dbf1d
model-00003-of-00059.safetensors4.81 GBa124cfa523ffdf6c02882f44fc9419ca891f8a8c6170787123afa913a9c663ec
model-00004-of-00059.safetensors4.81 GB636c86b0bf1ba940a7f32e4f2b3e36be2f50ef3221efa45df2b01f4e72bc4585
model-00005-of-00059.safetensors4.81 GB48d38897fd5726ae25a489fb888f76da4862880154ad2ed37abc004442971695
model-00006-of-00059.safetensors4.81 GBa8024f99a01c6cc52b5e3cab678e8e18f6077f1df4ec750afdc78018539a5894
model-00007-of-00059.safetensors4.81 GB284a34e315a91308b9e84394dd027f21e18eb35cae27c8949ba3ef24853bc5ea
model-00008-of-00059.safetensors4.81 GB17032a806898cb9615e080bab05bda3e5e863932e057b279c775f912e4ed1605
model-00009-of-00059.safetensors4.81 GBdcc84e3e525705fab85f8eaefe4ce2e69a6399fb63b76b6fcfc5fe55e6eb3bf3
model-00010-of-00059.safetensors4.81 GBf5337768358d785771187c8dc6dcea00ea70391170d866cd477dbbb92f165b97
model-00011-of-00059.safetensors4.81 GB7acb43109103dfc4a1021b43e898130e652e70898018b49aeaaf25f035a15841
model-00012-of-00059.safetensors4.81 GB875c9a5523173e0d2ae2ed7abde3a95b021cac1cffecf5d400d505aadc061032
model-00013-of-00059.safetensors4.81 GB67f2ad618e91929141c9299adc8f29d9934b812d426f08ddf85e692a9833c77f
model-00014-of-00059.safetensors4.81 GB428dfaae06c3e5739c807d0e0f1bd7bdbfff41f2dfcd4e4e695adfce92050070
model-00015-of-00059.safetensors4.81 GB8db4f2e385471db237e22933355e6e0bcc7f46500eee174e6d0edda9f240a181
model-00016-of-00059.safetensors4.81 GB0628246a502f5143460c4a3bc7d7e094c60c22f6b7f3fa8302ee21f2854a5445
model-00017-of-00059.safetensors4.81 GBc3af34bcf0c64214978ac0c69c04e0afc2027b9d1ffa9729abac3316d16a83c7
model-00018-of-00059.safetensors4.81 GBeab83aec0b55f27a91c2251cf678de1505a7cc4c7420e65a6a7820c3358e54f7
model-00019-of-00059.safetensors4.81 GBfd4eb8fff582c8d5197245725feebd76647c8c6a7d691d9970ce2e22a0bbe2b5
model-00020-of-00059.safetensors4.81 GBf092555ec809dc5e6fa6a1989d8d95b30f73ef7e83f12956a7d9f532385a0292
model-00021-of-00059.safetensors4.81 GBc7e6c4bb1d9b546123ba2819d4c47dd1866c79c13ba643929c80c9c4b1dc8faf
model-00022-of-00059.safetensors4.81 GB7cd6a28d9bfc93d6b83f77e11e3340d615a0cfc1760fc4ec7a1b4bb09847b028
model-00023-of-00059.safetensors4.81 GB25817204fb3a1c10276c0d8c6f3503c79388348ecb458740804352b75075d3cd
model-00024-of-00059.safetensors4.93 GB1a425a959d59723dde676a9121819788dd5f8d7aaae0e93bab9381ba8789729a
model-00025-of-00059.safetensors5.00 GBd8692ea80b7668a38dad83fc4be863b933f17da2b7ee0e12167761271f437634
model-00026-of-00059.safetensors5.00 GB4147e8cd43de8b2541c9655c6a846cacfea355f8f84fc74dfd4f1e5b27bb708a
model-00027-of-00059.safetensors4.93 GB43e5a174e86eb6759569426b59e6fa2e191f6d79a605b6de98fd1d0d51b2f447
model-00028-of-00059.safetensors4.81 GB571581317bdc6188143311fc98f348ff1742da5d3caf9e5fb4666bce7641ebf7
model-00029-of-00059.safetensors4.81 GB7081a4b7a8dbe4b2153ab945673bd64e4dbcb3e8ab342fa54cbe4d406d3c694a
model-00030-of-00059.safetensors4.81 GBbad6d9a1d4e0ce94e1c37cc0b3a11c27e19cd20cb70e6ec7c58c2dbec48e0da5
model-00031-of-00059.safetensors4.81 GB0baf3678b2019ce9f3c469166902a7cb5c4d2c9cf0d74d9aac2711b405e942c9
model-00032-of-00059.safetensors4.81 GBd2185b34b4f0e966b915cc779797984a8b12c7f88010ef767c8e9e9cf0c79565
model-00033-of-00059.safetensors4.81 GB3848b3acfbf4f6d384d07233348a7b68100fc928eb6a0f514bfd0131cf2ebf44
model-00034-of-00059.safetensors4.81 GBaa829c75a954b291c0de5fc2244727ada42f692d038d19ef8c890424635d1c6e
model-00035-of-00059.safetensors4.81 GBfaa68a0f1f0272c470853f643b934fadebeb7f71ed9b80746bfc824f7fe75e49
model-00036-of-00059.safetensors4.81 GBa3e0a006f69da252b0d760bcb79de478182d73b2ea93f2afcd57d98d52ba8b0d
model-00037-of-00059.safetensors4.81 GB7ef1a0d8420239ab78812b3d14fc99c1a99d0f364a0ea419dac7e187ae001b9a
model-00038-of-00059.safetensors4.81 GB82f18563cccd71b7d5c23b4774f1beb335de28e2260442f9032f9ad29e5674e4
model-00039-of-00059.safetensors4.81 GB427ca0a9f81e2a9af1465d6c7b8d6ebaf82d3b2637dd91cd8c1f61eaf204e7dd
model-00040-of-00059.safetensors4.81 GBc341cd9aad7b90118afa75c3b3336754d957de5a4a55190799049f1dd70be512
model-00041-of-00059.safetensors4.81 GB877dd428fba3d3b10d5f688626b21a356fdf23518f4be5e95c1aa596d70b2d46
model-00042-of-00059.safetensors4.81 GB33005e107da051dc59660e3aa4d29fb236e783849adf73049b2aecb59e9fefdb
model-00043-of-00059.safetensors4.81 GB6e8bdcf31f9f1925fb5673cfa9c40f07b59c3073b02f6c06c8ece6d27dc7f24c
model-00044-of-00059.safetensors4.81 GB68f0e70c784a929c513fdd8827bf9379a1f0919ce44d60ffcd573ccf81c2ef83
model-00045-of-00059.safetensors4.81 GB60f5d7d07c67c3ee7a7ee3991e7904434a4f890ae8ae1880373c9b5b7fa937cc
model-00046-of-00059.safetensors4.81 GBc4e97a90022efc665f629a61c20688e017a60521421ddf806ccb4960b45472ed
model-00047-of-00059.safetensors4.81 GBf08a72206280dd18942f06539b560f5afaed4ea836f64dd94b955555d688a350
model-00048-of-00059.safetensors4.81 GBf9d0e7a61ae135c505163dff5b2d2a60c9562189d21f70ccbff55eca473da939
model-00049-of-00059.safetensors4.81 GB1097db16182b48e0075f795a0f060a2033022e6ca35b4587e62a6fbffaf519c1
model-00050-of-00059.safetensors4.81 GB10263843a0b650ba91b4d914f47336b70d481d69173c5cd45d8e89905494ccb9
model-00051-of-00059.safetensors4.81 GBb3dc0078b77df7b906564e6250bdcb45c0c94c732098ac0a3ba16252a0ab68dd
model-00052-of-00059.safetensors4.93 GB1f380450d03b3416028da36798748b47a967da342c89b9223123631ef6000a6b
model-00053-of-00059.safetensors5.00 GB5f38d0bd1421a9515bbb48cd67d3e9a162348bacfda971fd6ce890ef8d62ee7d
model-00054-of-00059.safetensors5.00 GB146e06c298731ce4a307840e061f8398d0ced1b35c47e9dca2b43970ae218ebd
model-00055-of-00059.safetensors4.93 GBb0ac546077901ddbd30c92540900cac47b5b7bf15ae4154a4a4f1c1be7cb2000
model-00056-of-00059.safetensors4.81 GBdd6f426fb6fbaedd0d091218be5208157cf06939b1e84f77adde2233a7b8d6db
model-00057-of-00059.safetensors4.81 GBa87bb8d44a659d9506d54e7d3031751d775f7fda34ec2be9734d710e1195365e
model-00058-of-00059.safetensors4.81 GBf43f817664caadf7805dc8ebde0a7c7d0c55037850d0fc90b2b8310b55aa27d7
model-00059-of-00059.safetensors997 MB41b9558de05da48e40f2b13454462c6fe01fad2c7b15afd28104e526f531d22c
model.safetensors.index.json162 KB683424152c6867fc6d0ba639519dbadf1878e4c1e223af10b9645dba18c6a390
special_tokens_map.json414 B6fa06efa2785e450051989a6f8fb4416b10149ded485ddd3f127a40734f5cfd0
tokenizer.json1.80 MB11c08db21487c885d8c792180f0be237f6a261b89a46f128a6a80a3aa4bd1720
tokenizer.model493 KBdadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
tokenizer.model.v1493 KBdadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
tokenizer_config.json996 Bddb008229511e51607002ffe28925001c4a9ca4177dc4de3a655d085cc610b99
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
e1cd34ff17 pinned now manifest updated, same commit2026-11-14 21:24 UTC69 files · 281 GB
e1cd34ff172026-11-14 21:24 UTC69 files · 281 GB

Use it

$ fw get mistralai/Mixtral-8x22B-v0.1
# manifest sha256 02eb2757ba83… · 281 GB · 69 files
$ fw verify ./Mixtral-8x22B-v0.1 mistralai/Mixtral-8x22B-v0.1
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/mistralai/Mixtral-8x22B-v0.1.json --dir ./Mixtral-8x22B-v0.1 $ python3 fw.py verify ./Mixtral-8x22B-v0.1 ./mistralai__Mixtral-8x22B-v0.1.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download mistralai/Mixtral-8x22B-v0.1 --revision e1cd34ff1747406fb2277635ed25242803009bc2 --local-dir ./Mixtral-8x22B-v0.1

License

Name
Apache License 2.0
Id
Apache-2.0
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
License as declared by the publisher. No person read it. 2026-11-14
Text in
README.md
Text sha256
46fd106487e7081f035c5e1caed05f6a4df16689b4e901aa5d79e3b325b40e80
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: mistralai <huggingface.co/mistralai>Newsgroups: alt.freeweights.mistralSubject: Mixtral-8x22B-v0.1Date: 2026-11-14Commit: e1cd34fSigned: 2DC28CC7B26A283B ✓
Upstream
mistralai/Mixtral-8x22B-v0.1
Pinned commit
e1cd34ff1747406fb2277635ed25242803009bc2
Manifest
Mixtral-8x22B-v0.1.json · .minisig
Manifest sha256
02eb2757ba8372d6a584bb75a95c37c1f6e0b5e9271823778e2eac2fd9489630
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-14 21:24 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/mistralai/Mixtral-8x22B-v0.1.json $ curl -O https://freeweights.allternit.com/manifests/mistralai/Mixtral-8x22B-v0.1.json.minisig $ minisign -Vm Mixtral-8x22B-v0.1.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

1 model in the catalog name this one as their parent.

Fine-tunes
1
Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download mistralai/Mixtral-8x22B-v0.1
Open in Freeweights Studio

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

Signed manifest
minisign, key 2DC28CC7B26A283B. Mixtral-8x22B-v0.1.json. Provenance. Takedown history: none.
From: bartowski <huggingface.co/bartowski>Subject: alamios_Mistral-Small-3.1-DRAFT-0.5B-GGUF
From: microsoft <huggingface.co/microsoft>Subject: chatbench-mistral-7b
From: NousResearch <huggingface.co/NousResearch>Subject: DeepHermes-3-Mistral-24B-Preview
From: mistralai <huggingface.co/mistralai>Subject: Devstral-Small-2-24B-Instruct-2512
From: mlx-community <huggingface.co/mlx-community>Subject: Devstral-Small-2-24B-Instruct-2512-4bit
From: mlx-community <huggingface.co/mlx-community>Subject: Devstral-Small-2-24B-Instruct-2512-6bit