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mradermacher/SynthIA-v1.5-limarpv3-70B-i1-GGUF

sourceHugging Faceupdated 7mo agoView on Hugging Face

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Model Card

weighted/imatrix quants of https://huggingface.co/DS-Archive/SynthIA-v1.5-limarpv3-70B

*For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#SynthIA-v1.5-limarpv3-70B-i1-GGUF).*

static quants are available at https://huggingface.co/mradermacher/SynthIA-v1.5-limarpv3-70B-GGUF

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.

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

Link	Type	Size/GB	Notes
GGUF	i1-IQ1_S	15.0	for the desperate
GGUF	i1-IQ1_M	16.0	mostly desperate
GGUF	i1-IQ2_XXS	18.7
GGUF	i1-IQ2_XS	20.8
GGUF	i1-IQ2_S	21.8
GGUF	i1-IQ2_M	23.7
GGUF	i1-Q2_K	25.9	IQ3_XXS probably better
GGUF	i1-IQ3_XXS	27.0	lower quality
GGUF	i1-IQ3_XS	28.6
GGUF	i1-IQ3_S	30.3	beats Q3_K*
GGUF	i1-Q3KS	30.3	IQ3_XS probably better
GGUF	i1-IQ3_M	31.4
GGUF	i1-Q3KM	33.7	IQ3_S probably better
GGUF	i1-Q3KL	36.6	IQ3_M probably better
GGUF	i1-IQ4_XS	36.9
GGUF	i1-Q4_0	39.1	fast, low quality
GGUF	i1-Q4KS	39.7	optimal size/speed/quality
GGUF	i1-Q4KM	41.8	fast, recommended
GGUF	i1-Q5KS	47.9
GGUF	i1-Q5KM	49.2
PART 1 PART 2	i1-Q6_K	57.0	practically like static Q6_K

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

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

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

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.