How much VRAM does Qwen3-Coder-Next-DFlash need?

Q4_K_M is exactly 286,754,016 bytes (0.27 GiB) in weights. Add the KV cache, which depends on context length, plus roughly half a gigabyte of runtime overhead.

How large is Qwen3-Coder-Next-DFlash's KV cache?

0.50 GiB at 32K context with an f16 cache, computed per layer from the model's architecture. Quantizing the cache to q8_0 roughly halves it.

z-lab · text

Qwen3-Coder-Next-DFlash

z-lab/Qwen3-Coder-Next-DFlash

Qwen3-Coder-Next-DFlash at Q4_K_M is exactly 286,754,016 bytes (0.27 GiB / 0.29 GB) — an effective 4.840 bits per weight, not the nominal 4. Its KV cache at 32K is 0.50 GiB.

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

Parameters

474M

Architecture

dflash

8 layers

Context

262,144

native (config.json)

License

—

Shipped quantizations

● exact bytes, summed from published files

Quant	Size●	Exact bytes●	Effective bpw●	Tensors●	Publisher
Q4_0	0.25 GiB	272,696,544	4.603	—	transmutator
Q4_K_M	0.27 GiB	286,754,016	4.840	—	transmutator
Q5_K_M	0.32 GiB	339,182,816	5.725	—	transmutator
Q6_K	0.37 GiB	394,888,416	6.665	—	transmutator
Q8_0	0.47 GiB	509,674,720	8.602	—	transmutator
Q8_0	0.47 GiB	509,674,720	8.602	—	AtomicChat
BF16	0.89 GiB	954,008,800	16.102	—	transmutator

KV cache by context

computed per layer

Context	KV cache (f16)●	Flat formula	Overstated by	Full / windowed / recurrent
4,096	0.06 GiB	0.06 GiB	—	8 / 0 / 0
8,192	0.13 GiB	0.13 GiB	—	8 / 0 / 0
16,384	0.25 GiB	0.25 GiB	—	8 / 0 / 0
32,768	0.50 GiB	0.50 GiB	—	8 / 0 / 0
65,536	1.00 GiB	1.00 GiB	—	8 / 0 / 0
131,072	2.00 GiB	2.00 GiB	—	8 / 0 / 0

Compare with

same modality, comparable size

vs Llama-3.2-1B-Instruct vs ced-base vs gemma-3-1b-it vs Qwen3-1.7B vs embeddinggemma-300m vs Qwen3-0.6B 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 0.25 GiB. The real file is 0.27 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

128

Hidden size

2048

Vocab

151,936

Sliding window

none

SWA period

—

MLA

Experts

—

Experts per token

—

use_sliding_window

false

Questions people ask

How much VRAM does Qwen3-Coder-Next-DFlash need?: Q4_K_M is exactly 286,754,016 bytes (0.27 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is Qwen3-Coder-Next-DFlash's KV cache?: 0.50 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 Qwen3-Coder-Next-DFlash 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.