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MiniCPM-o-4_5

openbmb/MiniCPM-o-4_5

MiniCPM-o-4_5 at Q4_K_M is exactly 5,026,714,400 bytes (4.68 GiB / 5.03 GB) — an effective 4.291 bits per weight, not the nominal 4. Its KV cache at 32K is 4.50 GiB.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
9.4B
Architecture
qwen3
36 layers
Context
40,960
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
Q4_04.45 GiB4,773,679,9044.075openbmb
Q4_K_S4.47 GiB4,800,942,8804.098openbmb
Q4_K_M4.68 GiB5,026,714,4004.291openbmb
Q4_14.89 GiB5,246,637,8564.479openbmb
Q5_K_S5.33 GiB5,719,595,8084.882openbmb
Q5_05.33 GiB5,719,595,8084.882openbmb
Q5_K_M5.45 GiB5,849,946,9124.994openbmb
Q5_15.77 GiB6,192,553,7605.286openbmb
Q6_K6.26 GiB6,724,631,4565.740openbmb
Q8_08.11 GiB8,707,877,5367.433openbmb
F1615.26 GiB16,384,959,13613.987openbmb

KV cache by context

computed per layer
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.56 GiB0.56 GiB36 / 0 / 0
8,1921.13 GiB1.13 GiB36 / 0 / 0
16,3842.25 GiB2.25 GiB36 / 0 / 0
32,7684.50 GiB4.50 GiB36 / 0 / 0
65,5369.00 GiB9.00 GiB36 / 0 / 0
131,07218.00 GiB18.00 GiB36 / 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 4.91 GiB. The real file is 4.68 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
36
Attention heads
32
KV heads
8
Head dim
128
Hidden size
4096
Vocab
151,748
Sliding window
none
SWA period
MLA
no
Experts
Experts per token
use_sliding_window
false

Questions people ask

How much VRAM does MiniCPM-o-4_5 need?
Q4_K_M is exactly 5,026,714,400 bytes (4.68 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is MiniCPM-o-4_5's KV cache?
4.50 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 MiniCPM-o-4_5 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.