Qwen · text

Qwen2.5-Coder-7B-Instruct

Qwen/Qwen2.5-Coder-7B-Instruct

Qwen2.5-Coder-7B-Instruct at Q4_K_M is exactly 4,683,074,048 bytes (4.36 GiB / 4.68 GB) — an effective 4.919 bits per weight, not the nominal 4. Its KV cache at 32K is 1.75 GiB.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
7.6B
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_M2.59 GiB2,780,343,0722.921bartowski
Q2_K2.81 GiB3,015,940,0323.168Qwen
Q2_K2.81 GiB3,015,940,8963.168bartowski
IQ3_XS3.12 GiB3,346,256,6723.515bartowski
Q3_K_S3.25 GiB3,492,369,1843.669bartowski
Q2_K_L3.30 GiB3,548,164,8963.727bartowski
IQ3_M3.33 GiB3,574,012,7043.754bartowski
Q3_K_M3.55 GiB3,808,391,1044.001339Qwen
Q3_K_M3.55 GiB3,808,391,9684.001bartowski
Q3_K_L3.81 GiB4,088,459,7764.295lmstudio-community
Q3_K_L3.81 GiB4,088,460,0644.295bartowski
IQ4_XS3.93 GiB4,218,473,2484.431339bartowski
Q4_04.14 GiB4,444,121,8884.668339bartowski
Q4_K_S4.15 GiB4,457,769,7604.683bartowski
Q4_K_M4.36 GiB4,683,074,0484.919339lmstudio-community
Q4_K_M4.36 GiB4,683,074,3364.919339bartowski
Q4_K_L4.74 GiB5,087,564,5765.344bartowski
Q5_02 shards4.95 GiB5,315,176,5765.583Qwen
Q5_K_S4.95 GiB5,315,177,2485.583bartowski
Q5_K_M5.07 GiB5,444,832,0325.720339bartowski
Q5_K_L5.38 GiB5,781,197,6006.073bartowski
Q6_K5.82 GiB6,254,199,2966.570339lmstudio-community
Q6_K5.82 GiB6,254,199,5846.570339bartowski
Q6_K_L6.07 GiB6,518,182,6886.847bartowski
Q8_07.54 GiB8,098,525,6968.507339lmstudio-community
Q8_07.54 GiB8,098,525,9848.507339bartowski
Q4_03 shards8.25 GiB8,862,781,5689.310Qwen
Q4_K_M3 shards8.72 GiB9,366,147,2009.839Qwen
Q5_K_M3 shards10.14 GiB10,889,662,59211.439Qwen
Q6_K3 shards11.65 GiB12,508,397,69613.140Qwen
F1614.19 GiB15,237,853,69616.007339bartowski
Q8_04 shards15.08 GiB16,197,050,62417.015Qwen

KV cache by context

computed per layer
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.22 GiB0.22 GiB28 / 0 / 0
8,1920.44 GiB0.44 GiB28 / 0 / 0
16,3840.88 GiB0.88 GiB28 / 0 / 0
32,7681.75 GiB1.75 GiB28 / 0 / 0
65,5363.50 GiB3.50 GiB28 / 0 / 0
131,0727.00 GiB7.00 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 3.99 GiB. The real file is 4.36 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
28
Attention heads
28
KV heads
4
Head dim
128
Hidden size
3584
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-Coder-7B-Instruct need?
Q4_K_M is exactly 4,683,074,048 bytes (4.36 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-7B-Instruct's KV cache?
1.75 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-7B-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.