Monero · text

WizardLM-Uncensored-SuperCOT-StoryTelling-30b

Monero/WizardLM-Uncensored-SuperCOT-StoryTelling-30b

WizardLM-Uncensored-SuperCOT-StoryTelling-30b at Q4_K_M is exactly 19,621,149,152 bytes (18.27 GiB / 19.62 GB) — an effective 4.825 bits per weight, not the nominal 4. Its KV cache at 32K is 48.75 GiB.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
32.5B
Architecture
llama
60 layers
Context
2,048
native (config.json)
License
other

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
Q2_K12.58 GiB13,502,553,0563.321TheBloke
Q3_K_S13.10 GiB14,064,120,4483.459TheBloke
Q3_K_M14.68 GiB15,761,560,1923.876TheBloke
Q3_K_L16.09 GiB17,279,767,1684.250TheBloke
Q4_017.10 GiB18,355,976,6724.514TheBloke
Q4_K_S17.17 GiB18,437,765,6004.535TheBloke
Q4_K_M18.27 GiB19,621,149,1524.825TheBloke
Q5_K_S20.86 GiB22,395,370,7845.508TheBloke
Q5_020.86 GiB22,395,370,7845.508TheBloke
Q5_K_M21.46 GiB23,047,126,3045.668TheBloke
Q6_K24.85 GiB26,687,227,0406.563TheBloke
Q8_032.19 GiB34,565,138,7208.501TheBloke

KV cache by context

computed per layer
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0966.09 GiB6.09 GiB60 / 0 / 0
8,19212.19 GiB12.19 GiB60 / 0 / 0
16,38424.38 GiB24.38 GiB60 / 0 / 0
32,76848.75 GiB48.75 GiB60 / 0 / 0
65,53697.50 GiB97.50 GiB60 / 0 / 0
131,072195.00 GiB195.00 GiB60 / 0 / 0

Compare with

same modality, comparable size

Will it run on your card?

full quant x context sweep

Why other calculators give a different number

A parameters × bits ÷ 8 estimate puts Q4_K_M at roughly 17.04 GiB. The real file is 18.27 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
60
Attention heads
52
KV heads
52
Head dim
128
Hidden size
6656
Vocab
32,001
Sliding window
none
SWA period
MLA
no
Experts
Experts per token
use_sliding_window

Questions people ask

How much VRAM does WizardLM-Uncensored-SuperCOT-StoryTelling-30b need?
Q4_K_M is exactly 19,621,149,152 bytes (18.27 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is WizardLM-Uncensored-SuperCOT-StoryTelling-30b's KV cache?
48.75 GiB at 32K context with an f16 cache, computed per layer. Quantizing the cache to q8_0 roughly halves it, which is often the difference between a context length fitting and not.
Which quantization of WizardLM-Uncensored-SuperCOT-StoryTelling-30b should I use?
Q4_K_M is the usual default. Pick the largest quantization that fits your card at the context you actually need — the table above gives exact sizes for every one published.