huihui-ai · text

c4ai-command-r7b-12-2024-abliterated

huihui-ai/c4ai-command-r7b-12-2024-abliterated

c4ai-command-r7b-12-2024-abliterated at Q4_K_M is exactly 5,057,010,336 bytes (4.71 GiB / 5.06 GB) — an effective 5.039 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)
Parameters
8.0B
Architecture
cohere2
Context
native (config.json)
License
cc-by-nc-4.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ2_M2.87 GiB3,084,835,4883.074bartowski
Q2_K3.20 GiB3,438,533,2803.426bartowski
Q2_K_L3.44 GiB3,692,485,2803.680bartowski
IQ3_XS3.47 GiB3,724,794,5283.712bartowski
Q3_K_S3.60 GiB3,870,546,5923.857bartowski
IQ3_M3.72 GiB3,990,870,6883.977bartowski
Q3_K_M3.93 GiB4,224,965,2804.210bartowski
Q3_K_L4.22 GiB4,528,003,7444.512bartowski
IQ4_XS4.28 GiB4,600,355,4884.584bartowski
Q4_04.48 GiB4,812,167,8404.795bartowski
IQ4_NL4.48 GiB4,814,264,9924.798bartowski
Q4_K_S4.50 GiB4,828,945,0564.812bartowski
Q4_K_M4.71 GiB5,057,010,3365.039bartowski
Q4_14.87 GiB5,233,695,3925.215bartowski
Q4_K_L4.95 GiB5,310,962,3365.292bartowski
Q5_K_S5.28 GiB5,669,903,0085.650bartowski
Q5_K_M5.41 GiB5,803,596,4485.783bartowski
Q5_K_L5.64 GiB6,057,548,4486.036bartowski
Q6_K6.14 GiB6,596,844,1926.574bartowski
Q6_K_L6.38 GiB6,850,796,1926.827bartowski
Q8_07.95 GiB8,541,100,7048.511bartowski
BF1614.96 GiB16,067,254,65616.011bartowski

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 4.21 GiB. The real file is 4.71 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

Architecture unavailable — this repository is gated and no ungated mirror was found. Exact file sizes above are still authoritative; only the KV math needs the config.

Questions people ask

How much VRAM does c4ai-command-r7b-12-2024-abliterated need?
Q4_K_M is exactly 5,057,010,336 bytes (4.71 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of c4ai-command-r7b-12-2024-abliterated 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.