Qwen · text

Qwen2.5-Coder-1.5B-Instruct

Qwen/Qwen2.5-Coder-1.5B-Instruct

Qwen2.5-Coder-1.5B-Instruct at Q4_K_M is exactly 986,048,512 bytes (0.92 GiB / 0.99 GB) — an effective 5.110 bits per weight, not the nominal 4. Its KV cache at 32K is 0.88 GiB.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
1.5B
Architecture
qwen2
28 layers
Context
32,768
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ2_M0.56 GiB601,055,0083.115bartowski
Q2_K0.63 GiB676,305,1843.505bartowski
IQ3_XS0.68 GiB731,699,4883.792bartowski
Q2_K_L0.68 GiB732,825,3763.798bartowski
Q2_K0.70 GiB752,880,1923.902Qwen
Q3_K_S0.71 GiB760,944,9283.943bartowski
IQ3_M0.72 GiB776,664,3524.025bartowski
Q3_K_M0.77 GiB824,178,9764.271338bartowski
Q3_K_L0.82 GiB880,162,8164.561lmstudio-community
Q3_K_L0.82 GiB880,163,1044.561bartowski
IQ4_XS0.83 GiB895,732,0004.642338bartowski
Q3_K_M0.86 GiB924,456,0004.791339Qwen
Q4_00.87 GiB937,535,7764.859338bartowski
Q4_K_S0.88 GiB940,312,8644.873bartowski
Q4_K_M0.92 GiB986,048,5125.110lmstudio-community
Q4_K_M0.92 GiB986,048,8005.110338bartowski
Q4_K_L0.97 GiB1,042,568,9925.403bartowski
Q4_00.99 GiB1,066,227,2645.526339Qwen
Q5_K_S1.02 GiB1,098,729,7605.694bartowski
Q4_K_M1.04 GiB1,117,320,7685.790339Qwen
Q5_K_M1.05 GiB1,125,050,6565.830338bartowski
Q5_K_L1.10 GiB1,181,570,8486.123bartowski
Q5_01.17 GiB1,259,173,4406.525Qwen
Q6_K1.19 GiB1,272,739,8406.596lmstudio-community
Q6_K1.19 GiB1,272,740,1286.596338bartowski
Q5_K_M1.20 GiB1,285,494,3366.662339Qwen
Q6_K_L1.24 GiB1,329,260,3206.889bartowski
Q6_K1.36 GiB1,464,178,7527.588339Qwen
Q8_01.53 GiB1,646,573,0568.533338lmstudio-community
Q8_01.53 GiB1,646,573,3448.533bartowski
Q8_01.76 GiB1,894,532,1609.818339Qwen
F162.88 GiB3,093,669,37616.032338bartowski

KV cache by context

computed per layer
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.11 GiB0.11 GiB28 / 0 / 0
8,1920.22 GiB0.22 GiB28 / 0 / 0
16,3840.44 GiB0.44 GiB28 / 0 / 0
32,7680.88 GiB0.88 GiB28 / 0 / 0
65,5361.75 GiB1.75 GiB28 / 0 / 0
131,0723.50 GiB3.50 GiB28 / 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 0.81 GiB. The real file is 0.92 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
28
Attention heads
12
KV heads
2
Head dim
128
Hidden size
1536
Vocab
151,936
Sliding window
32768
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-Coder-1.5B-Instruct need?
Q4_K_M is exactly 986,048,512 bytes (0.92 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-Coder-1.5B-Instruct's KV cache?
0.88 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-Coder-1.5B-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.