mradermacher / Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF

huggingface.co
Total runs: 397
24-hour runs: -217
7-day runs: -379
30-day runs: -355
Model's Last Updated: 6月 16 2026
text-generation

Introduction of Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF

Model Details of Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF

About

static quants of https://huggingface.co/Agnuxo/Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF Q2_K 3.3
GGUF IQ3_XS 3.6
GGUF Q3_K_S 3.8
GGUF IQ3_S 3.8 beats Q3_K*
GGUF IQ3_M 3.9
GGUF Q3_K_M 4.1 lower quality
GGUF Q3_K_L 4.4
GGUF IQ4_XS 4.6
GGUF Q4_K_S 4.8 fast, recommended
GGUF Q4_K_M 5.0 fast, recommended
GGUF Q5_K_S 5.7
GGUF Q5_K_M 5.8
GGUF Q6_K 6.7 very good quality
GGUF Q8_0 8.6 fast, best quality
GGUF f16 16.2 16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH , for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.

Runs of mradermacher Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF on huggingface.co

397
Total runs
-217
24-hour runs
-195
3-day runs
-379
7-day runs
-355
30-day runs

More Information About Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF huggingface.co Model

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Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF huggingface.co

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Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF huggingface.co Url

https://huggingface.co/mradermacher/Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF

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https://huggingface.co/mradermacher/Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF

Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF install

Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF is an open source model from GitHub that offers a free installation service, and any user can find Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF on GitHub to install. At the same time, huggingface.co provides the effect of Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF install, users can directly use Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF install url in huggingface.co:

https://huggingface.co/mradermacher/Meta-Llama-3.1-8B-Instruct_CODE_Python_English_Asistant-16bit-v2-GGUF

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