How much VRAM does Qwen3-TTS-12Hz-1.7B-VoiceDesign need?

Q8_0 is exactly 2,042,225,536 bytes (1.90 GiB) in weights. Add the KV cache, which depends on context length, plus roughly half a gigabyte of runtime overhead.

Qwen · audio tts

Qwen3-TTS-12Hz-1.7B-VoiceDesign

Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign

Qwen3-TTS-12Hz-1.7B-VoiceDesign at Q8_0 is exactly 2,042,225,536 bytes (1.90 GiB / 2.04 GB) — an effective 8.524 bits per weight, not the nominal 8.

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

Parameters

1.9B

Architecture

qwen3tts

null layers

Context

—

native (config.json)

License

apache-2.0

Shipped quantizations

● exact bytes, summed from published files

Quant	Size●	Exact bytes●	Effective bpw●	Tensors●	Publisher
Q8_0	1.90 GiB	2,042,225,536	8.524	—	cstr
F16	3.58 GiB	3,838,976,832	16.023	—	cstr

Compare with

same modality, comparable size

vs Ace-Step1.5 vs Qwen3-TTS-12Hz-0.6B-Base vs OmniVoice vs orpheus-3b-0.1-ft vs s2-pro vs Fun-CosyVoice3-0.5B-2512 All alternatives →Will it fit on my card? →

Why other calculators give a different number

A parameters × bits ÷ 8 estimate puts Q8_0 at roughly 1.00 GiB. The real file is 1.90 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 Qwen3-TTS-12Hz-1.7B-VoiceDesign need?: Q8_0 is exactly 2,042,225,536 bytes (1.90 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of Qwen3-TTS-12Hz-1.7B-VoiceDesign 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.