How much VRAM does Qwen2.5-Omni-7B need?

Q4_K_M is exactly 4,683,072,384 bytes (4.36 GiB) in weights. Add the KV cache, which depends on context length, plus roughly half a gigabyte of runtime overhead.

Qwen · text

Qwen2.5-Omni-7B

Qwen/Qwen2.5-Omni-7B

Qwen2.5-Omni-7B at Q4_K_M is exactly 4,683,072,384 bytes (4.36 GiB / 4.68 GB) — an effective 3.491 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)From the file· KV per layer

Parameters

10.7B

Architecture

qwen2vl

null layers

Context

—

native (config.json)

License

other

Shipped quantizations

● exact bytes, summed from published files

Quant	Size●	Exact bytes●	Effective bpw●	Tensors●	Publisher
UD-IQ1_S	1.93 GiB	2,073,763,392	1.546	—	Sci-fi-vy
UD-IQ1_S	1.93 GiB	2,073,763,392	1.546	—	unsloth
UD-IQ1_M	2.05 GiB	2,200,536,640	1.640	—	unsloth
UD-IQ1_M	2.05 GiB	2,200,536,640	1.640	—	Sci-fi-vy
UD-IQ2_XXS	2.23 GiB	2,398,445,120	1.788	—	unsloth
UD-IQ2_XXS	2.23 GiB	2,398,445,120	1.788	—	Sci-fi-vy
UD-IQ2_M	2.66 GiB	2,856,250,944	2.129	—	unsloth
UD-IQ2_M	2.66 GiB	2,856,250,944	2.129	—	Sci-fi-vy
Q2_K	2.81 GiB	3,015,939,648	2.248	—	Sci-fi-vy
Q2_K	2.81 GiB	3,015,939,648	2.248	—	unsloth
Q2_K_L	2.93 GiB	3,143,673,408	2.343	—	Sci-fi-vy
Q2_K_L	2.93 GiB	3,143,673,408	2.343	—	unsloth
UD-IQ3_XXS	2.95 GiB	3,167,198,784	2.361	—	unsloth
UD-IQ3_XXS	2.95 GiB	3,167,198,784	2.361	—	Sci-fi-vy
Q3_K_S	3.25 GiB	3,492,367,936	2.603	—	unsloth
Q3_K_S	3.25 GiB	3,492,367,936	2.603	—	Sci-fi-vy
Q3_K_M	3.55 GiB	3,808,390,720	2.839	—	unsloth
Q3_K_M	3.55 GiB	3,808,390,720	2.839	—	Sci-fi-vy
IQ4_XS	3.94 GiB	4,235,503,168	3.157	—	Sci-fi-vy
IQ4_XS	3.94 GiB	4,235,503,168	3.157	—	unsloth
IQ4_NL	4.13 GiB	4,437,812,800	3.308	—	Sci-fi-vy
IQ4_NL	4.13 GiB	4,437,812,800	3.308	—	unsloth
Q4_K_S	4.15 GiB	4,457,768,512	3.323	—	Sci-fi-vy
Q4_K_S	4.15 GiB	4,457,768,512	3.323	—	unsloth
Q4_K_M	4.36 GiB	4,683,072,384	3.491	—	ggml-org
Q4_K_M	4.36 GiB	4,683,073,088	3.491	—	Sci-fi-vy
Q4_K_M	4.36 GiB	4,683,073,088	3.491	—	unsloth
Q4_1	4.54 GiB	4,873,283,136	3.633	—	unsloth
Q4_1	4.54 GiB	4,873,283,136	3.633	—	Sci-fi-vy
Q5_K_S	4.95 GiB	5,315,176,000	3.962	—	unsloth
Q5_K_S	4.95 GiB	5,315,176,000	3.962	—	Sci-fi-vy
Q5_K_M	5.07 GiB	5,444,830,784	4.059	—	Sci-fi-vy
Q5_K_M	5.07 GiB	5,444,830,784	4.059	—	unsloth
Q6_K	5.82 GiB	6,254,198,336	4.662	—	unsloth
Q6_K	5.82 GiB	6,254,198,336	4.662	—	Sci-fi-vy
Q8_0	7.54 GiB	8,098,524,032	6.037	—	ggml-org
Q8_0	7.54 GiB	8,098,524,736	6.037	—	unsloth
Q8_0	7.54 GiB	8,098,524,736	6.037	—	Sci-fi-vy
F16	14.19 GiB	15,237,852,032	11.359	—	ggml-org
BF16	14.19 GiB	15,237,852,480	11.359	—	Sci-fi-vy

Compare with

same modality, comparable size

vs gemma-4-E4B-it vs Qwen3-4B vs Qwen3-8B vs HyperCLOVAX-SEED-Text-Instruct-1.5B vs Llama-3.2-1B-Instruct vs Qwen3-VL-8B-Instruct-abliterated-v1 All alternatives →Will it fit on my card? →

Why other calculators give a different number

A parameters × bits ÷ 8 estimate puts Q4_K_M at roughly 5.62 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

—

Attention heads

—

KV heads

—

Head dim

—

Hidden size

—

Vocab

—

Sliding window

none

SWA period

—

MLA

Experts

—

Experts per token

—

use_sliding_window

—

Questions people ask

How much VRAM does Qwen2.5-Omni-7B need?: Q4_K_M is exactly 4,683,072,384 bytes (4.36 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of Qwen2.5-Omni-7B 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.