alt.freeweights.qwen / Qwen3-8B-Base
From: Qwen <huggingface.co/Qwen>Newsgroups: alt.freeweights.qwenSubject:

Qwen3-8B-Base

Date: 2026-11-14Commit: 49e3418Signed: 2DC28CC7B26A283B ✓

Text generation model with 8.2B parameters. Safetensors weights, 16.4 GB in all. Published by Qwen under Apache-2.0.

8.2B params16.4GBQwen3-8B-Basesafetensorspermissive
FactsParams8.2BSize16.4 GBFormatssafetensorsTasktext generationLicenseApache-2.0From sourcepermissive
$ fw get Qwen/Qwen3-8B-Base
# manifest sha256 966134e922db… · 16.4 GB · 14 files
$ fw verify ./Qwen3-8B-Base Qwen/Qwen3-8B-Base
From sourceHosted (signed)Qwen/Qwen3-8B-BaseLast check: 2026-11-14 21:12 UTC

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

Works with

Overview

Size
16.4 GB
Weights
16.4 GB (safetensors)
Parameters
8.2B
Formats
safetensors
Task
text generation
License
Apache-2.0 (permissive)
Files
14, each with a sha256
Publisher
Qwen
Added
2026-11-14
Section
alt.freeweights.qwen
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 21:12 UTCpassed

Model card

From the publisher at commit 49e3418. Shown as plain text with links; images open at the publisher.

Qwen3-8B-Base#

Qwen3 Highlights#

Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Building upon extensive advancements in training data, model architecture, and optimization techniques, Qwen3 delivers the following key improvements over the previously released Qwen2.5:

  • Expanded Higher-Quality Pre-training Corpus: Qwen3 is pre-trained on 36 trillion tokens across 119 languages — tripling the language coverage of Qwen2.5 — with a much richer mix of high-quality data, including coding, STEM, reasoning, book, multilingual, and synthetic data.
  • Training Techniques and Model Architecture: Qwen3 incorporates a series of training techiques and architectural refinements, including global-batch load balancing loss for MoE models and qk layernorm for all models, leading to improved stability and overall performance.
  • Three-stage Pre-training: Stage 1 focuses on broad language modeling and general knowledge acquisition, Stage 2 improves reasoning skills like STEM, coding, and logical reasoning, and Stage 3 enhances long-context comprehension by extending training sequence lengths up to 32k tokens.
  • Scaling Law Guided Hyperparameter Tuning: Through comprehensive scaling law studies across the three-stage pre-training pipeline, Qwen3 systematically tunes critical hyperparameters — such as learning rate scheduler and batch size — separately for dense and MoE models, resulting in better training dynamics and final performance across different model scales.

Model Overview#

Qwen3-8B-Base has the following features:

  • Type: Causal Language Models
  • Training Stage: Pretraining
  • Number of Parameters: 8.2B
  • Number of Paramaters (Non-Embedding): 6.95B
  • Number of Layers: 36
  • Number of Attention Heads (GQA): 32 for Q and 8 for KV
  • Context Length: 32,768

For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our blog, GitHub, and Documentation.

Requirements#

The code of Qwen3 has been in the latest Hugging Face transformers and we advise you to use the latest version of transformers.

With transformers<4.51.0, you will encounter the following error:

KeyError: 'qwen3'

Evaluation & Performance#

Detailed evaluation results are reported in this 📑 blog.

Citation#

If you find our work helpful, feel free to give us a cite.

@misc{qwen3technicalreport,
      title={Qwen3 Technical Report}, 
      author={Qwen Team},
      year={2025},
      eprint={2505.09388},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2505.09388}, 
}

Files

14 files · 16.4 GBWeights 16.4 GB (safetensors). Sizes and sha256 from the signed manifest.
Hide all 14 files with their sha256
FileSizesha256
.gitattributes1.52 KB11ad7efa24975ee4b0c3c3a38ed18737f0658a5f75a0a96787b576a78a023361
README.md2.94 KB0eb9f991baa4f92c9ef708d1e9c7a01ae5b19d05516d38f8833549aa8b06a07e
config.json729 B3bd01d7ad7a2e203ecbbe84e24087a51c6d2a108ee4bcc42d0016bf49564983a
generation_config.json138 B8c970692323e3ea0e9b8b0a4dca79388d31226e41f83c9fd6014804280ebf6e8
merges.txt1.67 MB8831e4f1a044471340f7c0a83d7bd71306a5b867e95fd870f74d0c5308a904d5
model-00001-of-00005.safetensors4.00 GB9983f1b9ef2f60e7c3730d9bc11ada914e6ec630639b5b020a89bd158cd0446b
model-00002-of-00005.safetensors3.99 GB9aa12339835bf7a093d3d0b0a0d2d77f8538301cfc7f8e7ec7a585858ebf7a1f
model-00003-of-00005.safetensors3.96 GBc7dd5a191c8da555def0714550375b3c0117751add408fcdda0c2a79ac0186bc
model-00004-of-00005.safetensors3.19 GBad8b708792105133e03fe19e2d56c89c709f677f01285f8b3ede8947d59fd9fe
model-00005-of-00005.safetensors1.24 GBfbf24915d47ea030bb68ab0b9488f4515a907185baa6dc26837c9c3f2326a550
model.safetensors.index.json32.9 KBcd39d5e44c5aadfd1954b598883aea1c4a98822a2f7723d214ef2278b7fec2e4
tokenizer.json7.03 MBc0382117ea329cdf097041132f6d735924b697924d6f6fc3945713e96ce87539
tokenizer_config.json9.68 KB3c04ed3ca964ea2f6b2b5faf0dc4d31aec1cb1e8b4bcf63f402d295046b422b5
vocab.json2.78 MBca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
49e3418fbb pinned now manifest updated, same commit2026-11-14 21:12 UTC14 files · 16.4 GB
49e3418fbb2026-11-14 21:12 UTC14 files · 16.4 GB

Use it

$ fw get Qwen/Qwen3-8B-Base
# manifest sha256 966134e922db… · 16.4 GB · 14 files
$ fw verify ./Qwen3-8B-Base Qwen/Qwen3-8B-Base
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/Qwen/Qwen3-8B-Base.json --dir ./Qwen3-8B-Base $ python3 fw.py verify ./Qwen3-8B-Base ./Qwen__Qwen3-8B-Base.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download Qwen/Qwen3-8B-Base --revision 49e3418fbbbca6ecbdf9608b4d22e5a407081db4 --local-dir ./Qwen3-8B-Base
transformersLoad the weights in Python.
import os os.environ["HF_ENDPOINT"] = "https://freeweights.allternit.com" from transformers import AutoModelForCausalLM, AutoTokenizer tok = AutoTokenizer.from_pretrained("Qwen/Qwen3-8B-Base", revision="49e3418fbbbca6ecbdf9608b4d22e5a407081db4") model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-8B-Base", revision="49e3418fbbbca6ecbdf9608b4d22e5a407081db4", device_map="auto")
vLLMServe an OpenAI-compatible API.
$ HF_ENDPOINT=https://freeweights.allternit.com vllm serve Qwen/Qwen3-8B-Base --revision 49e3418fbbbca6ecbdf9608b4d22e5a407081db4

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
0eb9f991baa4f92c9ef708d1e9c7a01ae5b19d05516d38f8833549aa8b06a07e
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: Qwen <huggingface.co/Qwen>Newsgroups: alt.freeweights.qwenSubject: Qwen3-8B-BaseDate: 2026-11-14Commit: 49e3418Signed: 2DC28CC7B26A283B ✓
Upstream
Qwen/Qwen3-8B-Base
Pinned commit
49e3418fbbbca6ecbdf9608b4d22e5a407081db4
Manifest
Qwen3-8B-Base.json · .minisig
Manifest sha256
966134e922dbfc809a622e16eff6a5b30247bb24a78e835b3e7a4d2d67360882
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-14 21:12 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/Qwen/Qwen3-8B-Base.json $ curl -O https://freeweights.allternit.com/manifests/Qwen/Qwen3-8B-Base.json.minisig $ minisign -Vm Qwen3-8B-Base.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

11 models in the catalog name this one as their parent.

Fine-tunes
7
Quantizations
4
Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download Qwen/Qwen3-8B-Base
Open in Freeweights Studio

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

Signed manifest
minisign, key 2DC28CC7B26A283B. Qwen3-8B-Base.json. Provenance. Takedown history: none.

Variants

4 quantized or adapter builds of Qwen3-8B-Base. Each has its own license check and page.

From: BAAI <huggingface.co/BAAI>Subject: Aquila-VL-2B-llava-qwen
From: Perciqa <huggingface.co/Perciqa>Subject: Aurora-Code-1
From: BAAI <huggingface.co/BAAI>Subject: bge-reasoner-embed-qwen3-8b-0923
From: amazon <huggingface.co/amazon>Subject: BMOJOF-primed-HQwen3-8B-Instruct
From: nbeerbower <huggingface.co/nbeerbower>Subject: Bubba-Qwen3.6-27B-LoRA
From: bartowski <huggingface.co/bartowski>Subject: bytkim_Qwen3.8-27B-pi-GGUF