Meta-Llama-3.1-8B-Instruct-GGUF GGUF download | Hugging Bay

Q: What is this model?

QuantFactory/Meta-Llama-3.1-8B-Instruct-GGUF is an open-weights language model for text generation published by QuantFactory, added to Hugging Bay Sep 18, 2026. Model from Hugging Face for text generation: QuantFactory/Meta-Llama-3.1-8B-Instruct-GGUF · pytorch

Q: Can I use it commercially?

It is released under the llama3.1 license. Commercial use is allowed with conditions. Commercial use is permitted with obligations: Llama community license: commercial use allowed; if your products/services exceeded 700 million monthly active users (Section 2, Additional Commercial Terms) you must request a license from Meta first; the acceptable-use policy and attribution notice apply.

Q: How big is it?

QuantFactory/Meta-Llama-3.1-8B-Instruct-GGUF has 8B parameters. Hosted here: 1 file, 4.92 GB. Full repo upstream: 64.4 GB. The recommended download, Meta-Llama-3.1-8B-Instruct.Q4_K_M.gguf (Q4_K_M), is 4.92 GB.

Q: What can I download here?

Hosted here: 1 file, 4.92 GB. Full repo upstream: 64.4 GB. The original release is at https://huggingface.co/QuantFactory/Meta-Llama-3.1-8B-Instruct-GGUF.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 1 hosted file carries a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-quantfactory-meta-llama-3-1-8b-instruct-gguf/safety on Hugging Bay.

Q: Will QuantFactory/Meta-Llama-3.1-8B-Instruct-GGUF run on my computer?

We can’t check the fit; we don’t know your machine. We don’t have your machine’s specs, so no check ran and no verdict is shown. Answer two quick questions and we’ll estimate, from the memory you tell us, whether it fits your machine. Or skip it; you can still download; fit isn’t checked.

QuantFactory

Meta-Llama-3.1-8B-Instruct-GGUF

QuantFactory/Meta-Llama-3.1-8B-Instruct-GGUF

text generationLicense: llama3.1Hashes recordedGGUF

Content controls: not assessed.

Model from Hugging Face for text generation: QuantFactory/Meta-Llama-3.1-8B-Instruct-GGUF · pytorch

View as JSON →

1 hosted of 14 listed

Hashes recorded. Date not recorded.

File	Tamanho	SHA-256	Origem	Baixar
Weights
`Meta-Llama-3.1-8B-Instruct.Q4_K_M.gguf` Default	4.92 GB	`6d86fb9d…8687e5fa` `6d86fb9d2910178f5c744234fdf91910e033ef7b03c5e23dcc6d25e98687e5fa`	Hosted	Baixar
`Meta-Llama-3.1-8B-Instruct.Q2_K.gguf`	3.18 GB	`c34cfed2…a0f5f04d` `c34cfed2633ad8d9c6796d8d4573855568ec746ad300c91e9c60a63ca0f5f04d`	Upstream only	File metadata
`Meta-Llama-3.1-8B-Instruct.Q3_K_L.gguf`	4.32 GB	`c00dad02…4d8f7fd1` `c00dad02eefb83c5a045b87a914354736f9f967d5fcf95e96fbc25f54d8f7fd1`	Upstream only	File metadata
`Meta-Llama-3.1-8B-Instruct.Q3_K_M.gguf`	4.02 GB	`7ed53ec5…6c076311` `7ed53ec5774dab6bc0f39510a60542e3ff8f1e129bb17571253030b86c076311`	Upstream only	File metadata
`Meta-Llama-3.1-8B-Instruct.Q4_0.gguf`	4.66 GB	`263cdd04…4409837f` `263cdd049fcaa2443f159e885330bc33de757a5d883658678d97373f4409837f`	Upstream only	File metadata
`Meta-Llama-3.1-8B-Instruct.Q4_1.gguf`	5.13 GB	`1a9f1808…1da064b6` `1a9f180809d4d3663dcee78a378d3b377a6131aab19ff5f720898def1da064b6`	Upstream only	File metadata
`Meta-Llama-3.1-8B-Instruct.Q5_0.gguf`	5.6 GB	`565dc233…b2bd884d` `565dc2331870c79d58a1f944c7b64daa9597f77b1b56aace38f0dc7db2bd884d`	Upstream only	File metadata
`Meta-Llama-3.1-8B-Instruct.Q5_1.gguf`	6.07 GB	`d63cd26e…5e234fa0` `d63cd26ebd385a4528e7537e6fad13a7774354ae535f976e3f70a67d5e234fa0`	Upstream only	File metadata
`Meta-Llama-3.1-8B-Instruct.Q5_K_M.gguf`	5.73 GB	`599b0d4a…6a43fa08` `599b0d4a087814be765d1d607b2c7bd315868dcc96dbc00c45f877bc6a43fa08`	Upstream only	File metadata
`Meta-Llama-3.1-8B-Instruct.Q5_K_S.gguf`	5.6 GB	`45896014…5e82caef` `458960148f3909fb71c5d6036ff932e95d2ae695a2cc2fc2f8854fef5e82caef`	Upstream only	File metadata
`Meta-Llama-3.1-8B-Instruct.Q6_K.gguf`	6.6 GB	`88a24c7c…7814ee32` `88a24c7c7dac554685659340c28d92a2b87f5ae2973bb1c22aa573987814ee32`	Upstream only	File metadata
`Meta-Llama-3.1-8B-Instruct.Q8_0.gguf`	8.54 GB	`e240fae3…72fa48cc` `e240fae33a33be0a820880e81239938f7a28e49010487a14a9f04ac672fa48cc`	Upstream only	File metadata
Docs
`.gitattributes`	2.4 KB	—	Upstream only	File metadata
`README.md`	41.8 KB	—	Upstream only	File metadata

Verificar um download

In the folder where you saved Meta-Llama-3.1-8B-Instruct.Q4_K_M.gguf, run:

macOS

shasum -a 256 -- 'Meta-Llama-3.1-8B-Instruct.Q4_K_M.gguf'

Linux

sha256sum -- 'Meta-Llama-3.1-8B-Instruct.Q4_K_M.gguf'

Windows

Get-FileHash -LiteralPath 'Meta-Llama-3.1-8B-Instruct.Q4_K_M.gguf' -Algorithm SHA256

Compare the result with the recorded SHA-256.

Meta-Llama-3.1-8B-Instruct-GGUF

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