ModelHub XC 9d18e60749 初始化项目,由ModelHub XC社区提供模型
Model: mradermacher/Reflection-Llama-3.1-8B-GGUF
Source: Original Platform
2026-04-13 23:33:04 +08:00

base_model, language, library_name, license, quantized_by, tags
base_model language library_name license quantized_by tags
terrycraddock/Reflection-Llama-3.1-8B
en
transformers apache-2.0 mradermacher
unsloth

About

static quants of https://huggingface.co/terrycraddock/Reflection-Llama-3.1-8B

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Reflection-Llama-3.1-8B-i1-GGUF

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
PART 1 PART 2 Q2_K 6.5
PART 1 PART 2 IQ3_XS 7.1
PART 1 PART 2 Q3_K_S 7.4
PART 1 PART 2 IQ3_S 7.5 beats Q3_K*
PART 1 PART 2 IQ3_M 7.7
PART 1 PART 2 Q3_K_M 8.1 lower quality
PART 1 PART 2 Q3_K_L 8.7
PART 1 PART 2 IQ4_XS 9.1
PART 1 PART 2 Q4_K_S 9.5 fast, recommended
PART 1 PART 2 Q4_K_M 9.9 fast, recommended
PART 1 PART 2 Q5_K_S 11.3
PART 1 PART 2 Q5_K_M 11.6
PART 1 PART 2 Q6_K 13.3 very good quality
PART 1 PART 2 Q8_0 17.2 fast, best quality

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.

Description
Model synced from source: mradermacher/Reflection-Llama-3.1-8B-GGUF
Readme 29 KiB