Qwen · text

Qwen2.5-14B-Instruct

Qwen/Qwen2.5-14B-Instruct

Qwen2.5-14B-Instruct at Q4_K_M is exactly 8,988,110,496 bytes (8.37 GiB / 8.99 GB) — an effective 4.868 bits per weight, not the nominal 4. Its KV cache at 32K is 6.00 GiB.

From the file· summed from 3 file(s)From the file· KV per layer
Parameters
14.8B
Architecture
qwen2
48 layers
Context
32,768
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ2_M4.99 GiB5,356,146,8162.901bartowski
Q2_K2 shards5.37 GiB5,770,497,6003.126Qwen
Q2_K5.37 GiB5,770,498,1763.126bartowski
IQ3_XS5.94 GiB6,383,362,1763.458bartowski
Q2_K_L6.08 GiB6,530,818,1763.537bartowski
Q3_K_S6.20 GiB6,659,596,4163.607bartowski
IQ3_M6.44 GiB6,916,538,4963.746bartowski
Q3_K_M2 shards6.84 GiB7,339,204,1603.975Qwen
Q3_K_M6.84 GiB7,339,204,7363.975579bartowski
Q3_K_L7.38 GiB7,924,768,6084.292lmstudio-community
Q3_K_L7.38 GiB7,924,768,8964.292bartowski
IQ4_XS7.56 GiB8,119,840,8964.398579bartowski
Q4_03 shards7.93 GiB8,517,725,8564.614Qwen
Q4_07.96 GiB8,544,268,4164.628579bartowski
Q4_K_S7.98 GiB8,573,431,9364.644bartowski
Q4_K_M3 shards8.37 GiB8,988,110,4964.868Qwen
Q4_K_M8.37 GiB8,988,110,6884.868579lmstudio-community
Q4_K_M8.37 GiB8,988,110,9764.868579bartowski
Q4_K_L8.91 GiB9,565,954,1765.181bartowski
Q5_03 shards9.56 GiB10,266,554,0485.561Qwen
Q5_K_S9.56 GiB10,266,554,4965.561bartowski
Q5_K_M3 shards9.79 GiB10,508,873,3765.692Qwen
Q5_K_M9.79 GiB10,508,873,8565.692579bartowski
Q5_K_L10.23 GiB10,989,396,0965.952bartowski
Q6_K4 shards11.29 GiB12,124,684,0646.567Qwen
Q6_K11.29 GiB12,124,684,1286.567579lmstudio-community
Q6_K11.29 GiB12,124,684,4166.567579bartowski
Q6_K_L11.64 GiB12,501,803,1366.771bartowski
Q8_04 shards14.62 GiB15,701,597,9848.505Qwen
Q8_014.62 GiB15,701,598,0488.505579lmstudio-community
Q8_014.62 GiB15,701,598,3368.505579bartowski
F1627.52 GiB29,547,716,44816.004579bartowski

KV cache by context

computed per layer
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.75 GiB0.75 GiB48 / 0 / 0
8,1921.50 GiB1.50 GiB48 / 0 / 0
16,3843.00 GiB3.00 GiB48 / 0 / 0
32,7686.00 GiB6.00 GiB48 / 0 / 0
65,53612.00 GiB12.00 GiB48 / 0 / 0
131,07224.00 GiB24.00 GiB48 / 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 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

from config.json
Layers
48
Attention heads
40
KV heads
8
Head dim
128
Hidden size
5120
Vocab
152,064
Sliding window
131072
SWA period
MLA
no
Experts
Experts per token
use_sliding_window
false

This model declares a sliding window but sets use_sliding_window: false, so the window is not applied. Honouring the field without the flag understates KV for the whole family.

Questions people ask

How much VRAM does Qwen2.5-14B-Instruct need?
Q4_K_M is exactly 8,988,110,496 bytes (8.37 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is Qwen2.5-14B-Instruct's KV cache?
6.00 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 Qwen2.5-14B-Instruct 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.