Crazy-AI-Model · mradermacher

Crazy-AI-Model Q8_0

This file is exactly 8,098,525,952 bytes — 7.54 GiB / 8.10 GB at an effective 8.507 bits per weight. The nominal rate for Q8_0 is lower; mixed-precision tensors make the real figure higher, always.

From the file· 1 file(s), summed

Get it

7.54 GiB · 1 file
llama.cpp
llama-cli -hf mradermacher/Crazy-AI-Model-GGUF:Q8_0

Downloads and runs in one step, resolving the quantization by name.

Hugging Face CLI
hf download mradermacher/Crazy-AI-Model-GGUF Crazy-AI-Model.Q8_0.gguf
Direct download

Straight from the Hugging Face CDN — we host nothing and earn nothing from this. Verify what you received against the exact byte count above; a size mismatch is the usual cause of a file that will not load.

Size
7.54 GiB
8.10 GB
Effective bpw
8.507
from real bytes ÷ params
Tensors
Header
GGUF metadata

Fit by accelerator

AcceleratorMemoryTotal @4KTotal @32KFitstok/s @4K
Arc A310 4GB4 GB8.62 GiB10.15 GiBno
Arc A350M 4GB4 GB8.62 GiB10.15 GiBno
Arc A370M 4GB4 GB8.62 GiB10.15 GiBno
Arc A530M 4GB4 GB8.62 GiB10.15 GiBno
Arc Pro A30M 4GB4 GB8.62 GiB10.15 GiBno
Radeon Pro W64004 GB8.72 GiB10.25 GiBno
Radeon RX 64004 GB8.72 GiB10.25 GiBno
Radeon RX 6500 XT4 GB8.72 GiB10.25 GiBno
RTX A4004 GB8.82 GiB10.35 GiBno
Arc A380 6GB6 GB8.62 GiB10.15 GiBno
Arc Pro A40 6GB6 GB8.62 GiB10.15 GiBno
Arc Pro A50 6GB6 GB8.62 GiB10.15 GiBno
GeForce RTX 20606 GB8.62 GiB10.15 GiBno
GeForce RTX 30506 GB8.62 GiB10.15 GiBno
GeForce RTX 3060 OEM6 GB8.62 GiB10.15 GiBno
RTX A20006 GB8.82 GiB10.35 GiBno
Apple M18 GB8.37 GiB9.90 GiBno
Apple M28 GB8.37 GiB9.90 GiBno
Apple M38 GB8.37 GiB9.90 GiBno
Apple M48 GB8.37 GiB9.90 GiBno
Arc A530M 8GB8 GB8.62 GiB10.15 GiBno
Arc A550M 8GB8 GB8.62 GiB10.15 GiBno
Arc A570M 8GB8 GB8.62 GiB10.15 GiBno
Arc A580 8GB8 GB8.62 GiB10.15 GiBno
Spec sheetPredictedwhat these mean

Memory at context

ContextWeightsKV (f16)KV (q8_0)Working bufferTotal (f16)
4,0967.54 GiB0.22 GiB0.12 GiB0.35 GiB8.12 GiB
8,1927.54 GiB0.44 GiB0.23 GiB0.35 GiB8.33 GiB
16,3847.54 GiB0.88 GiB0.46 GiB0.35 GiB8.77 GiB
32,7687.54 GiB1.75 GiB0.93 GiB0.35 GiB9.65 GiB
65,5367.54 GiB3.50 GiB1.86 GiB0.35 GiB11.40 GiB
131,0727.54 GiB7.00 GiB3.72 GiB0.35 GiB14.90 GiB
From the filePredictedwhat these mean

Quantizing the KV cache to q8_0 is a roughly 2× lever on the dominant term at long context, and it is the single most useful setting most local users never touch. Totals here exclude the allocator reserve your driver takes, which is hardware-specific — the per-accelerator table above includes it.