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Nous-Hermes-Llama2-70b

NousResearch/Nous-Hermes-Llama2-70b

Nous-Hermes-Llama2-70b at Q4_K_M is exactly 41,422,921,728 bytes (38.58 GiB / 41.42 GB) — an effective 4.804 bits per weight, not the nominal 4. Its KV cache at 32K is 10.00 GiB.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
69.0B
Architecture
llama
80 layers
Context
4,096
native (config.json)
License
mit

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
I1-IQ1_S13.54 GiB14,535,546,0161.686mradermacher
I1-IQ1_M14.85 GiB15,943,259,2961.849mradermacher
I1-IQ2_XXS17.03 GiB18,289,448,0962.121mradermacher
I1-IQ2_XS18.94 GiB20,334,171,2962.358mradermacher
I1-IQ2_S19.89 GiB21,354,321,8882.477mradermacher
I1-IQ2_M21.64 GiB23,231,272,9282.694mradermacher
I1-Q2_K23.71 GiB25,462,446,3042.953mradermacher
I1-IQ3_XXS24.76 GiB26,581,473,2483.083mradermacher
I1-IQ3_XS26.37 GiB28,314,983,4563.284mradermacher
Q2_K27.27 GiB29,279,262,8483.396TheBloke
Q3_K_S27.86 GiB29,919,304,6403.470TheBloke
I1-Q3_K_S27.86 GiB29,919,304,7363.470mradermacher
I1-IQ3_S27.86 GiB29,919,304,7363.470mradermacher
I1-IQ3_M28.82 GiB30,944,287,7763.589mradermacher
Q3_K_M30.91 GiB33,186,667,4563.849TheBloke
I1-Q3_K_M30.99 GiB33,274,747,9363.859mradermacher
Q3_K_L33.67 GiB36,147,846,0804.192TheBloke
I1-Q3_K_L33.67 GiB36,147,846,1764.192mradermacher
I1-IQ4_XS34.30 GiB36,829,831,0084.272mradermacher
Q4_036.20 GiB38,872,260,6084.508TheBloke
I1-Q4_036.34 GiB39,019,061,3444.526mradermacher
Q4_K_S36.39 GiB39,073,587,2004.532TheBloke
I1-Q4_K_S36.55 GiB39,249,748,0644.552mradermacher
Q4_K_M38.58 GiB41,422,921,7284.804TheBloke
I1-Q4_K_M38.58 GiB41,422,921,8244.804mradermacher
Q5_044.20 GiB47,461,409,7925.505TheBloke
Q5_K_S44.20 GiB47,461,409,7925.505TheBloke
I1-Q5_K_S44.20 GiB47,461,409,8885.505mradermacher
Q5_K_M45.41 GiB48,753,779,7125.654TheBloke
I1-Q5_K_M45.41 GiB48,753,779,8085.654mradermacher

KV cache by context

computed per layer
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0961.25 GiB1.25 GiB80 / 0 / 0
8,1922.50 GiB2.50 GiB80 / 0 / 0
16,3845.00 GiB5.00 GiB80 / 0 / 0
32,76810.00 GiB10.00 GiB80 / 0 / 0
65,53620.00 GiB20.00 GiB80 / 0 / 0
131,07240.00 GiB40.00 GiB80 / 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 36.13 GiB. The real file is 38.58 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
80
Attention heads
64
KV heads
8
Head dim
128
Hidden size
8192
Vocab
32,001
Sliding window
none
SWA period
MLA
no
Experts
Experts per token
use_sliding_window

Questions people ask

How much VRAM does Nous-Hermes-Llama2-70b need?
Q4_K_M is exactly 41,422,921,728 bytes (38.58 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is Nous-Hermes-Llama2-70b's KV cache?
10.00 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 Nous-Hermes-Llama2-70b 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.