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Rombos-LLM-V2.5-Qwen-14b

rombodawg/Rombos-LLM-V2.5-Qwen-14b

Rombos-LLM-V2.5-Qwen-14b at Q4_K_M is exactly 8,988,110,752 bytes (8.37 GiB / 8.99 GB) — an effective 4.868 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)
Parameters
14.8B
Architecture
qwen2
Context
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ2_S4.66 GiB5,003,726,7522.710bartowski
IQ2_M4.99 GiB5,356,146,5922.901bartowski
Q2_K5.37 GiB5,770,497,9523.126bartowski
IQ3_XS5.94 GiB6,383,361,9523.458bartowski
Q2_K_L6.08 GiB6,530,817,9523.537bartowski
Q3_K_S6.20 GiB6,659,596,1923.607bartowski
IQ3_M6.44 GiB6,916,538,2723.746bartowski
Q3_K_M6.84 GiB7,339,204,5123.975bartowski
Q3_K_L7.38 GiB7,924,768,6724.292bartowski
IQ4_XS7.56 GiB8,119,840,6724.398bartowski
Q4_07.96 GiB8,544,268,1924.628bartowski
Q4_K_S7.98 GiB8,573,431,7124.644bartowski
Q4_K_M8.37 GiB8,988,110,7524.868bartowski
Q4_K_L8.91 GiB9,565,953,9525.181bartowski
Q5_K_S9.56 GiB10,266,554,2725.561bartowski
Q5_K_M9.79 GiB10,508,873,6325.692bartowski
Q5_K_L10.23 GiB10,989,395,8725.952bartowski
Q6_K11.29 GiB12,124,684,1926.567bartowski
Q6_K_L11.64 GiB12,501,802,9126.771bartowski
Q8_014.62 GiB15,701,598,1128.505bartowski
F1627.52 GiB29,547,716,22416.004bartowski

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 7.74 GiB. The real file is 8.37 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 Rombos-LLM-V2.5-Qwen-14b need?
Q4_K_M is exactly 8,988,110,752 bytes (8.37 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of Rombos-LLM-V2.5-Qwen-14b 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.