How much memory do I need to run Qwen3.8-Flash-Next-DS4-Q4 (Q4_1)?

The file size is 32.0 GB (measured). With a 8,192-token context, the estimated memory including the KV cache is 33.4 GB. The formula is published at https://localllm.az-arte.com/en/guide/memory-calculation.

Does Qwen3.8-Flash-Next-DS4-Q4 run in 8 GB, 12 GB, 16 GB or 24 GB of VRAM?

8 GB: no quantization fits; 12 GB: no quantization fits; 16 GB: no quantization fits; 24 GB: no quantization fits (estimated at 8,192 tokens with an f16 KV cache, files from the most-downloaded source).

ivanfioravanti

Qwen3.8-Flash-Next-DS4-Q4

Parameters: 51.2B
Architecture: qwen4-exp-ple
License: Conditional

Base model: Qwen/Qwen3.8-Flash-Next
License: qwen-community-1.0

Memory needed to run Q4_1 at 8K tokens

33.4 GB Estimated

File size 32.0 GB Measured

VRAM it fits in (rough guide)

8 GB does not fit
12 GB does not fit
16 GB does not fit
24 GB does not fit
32 GB fits
48 GB fits

See devices and models for 32 GB

Macs cap how much memory the GPU can use, so leave headroom in unified memory.

Data as of Oct 9, 2026

About Qwen3.8-Flash-Next-DS4-Q4

Qwen3.8-Flash-Next-DS4-Q4 is a GGUF model based on Qwen/Qwen3.8-Flash-Next on Hugging Face. GGUF files are published by ivanfioravanti/Qwen3.8-Flash-Next-DS4-Q4. It has about 51.2B parameters, the qwen4-exp-ple architecture (values written in the GGUF).

There is one quantization, Q4_1, with a file size of 32.0 GB (actual size on Hugging Face).

Running Q4_1 (32.0 GB) with an 8,192-token context needs an estimated 33.4 GB of memory, and an estimated 34.1 GB at 32,768 tokens. For 8,192 tokens, a GPU with 32 GB or more of VRAM (such as GeForce RTX 5090), or a Mac with 32 GB or more of unified memory, is a rough guide (macOS caps how much memory the GPU can use, so leave some headroom).

The original model is licensed under Qwen Community License 1.0, which allows commercial use with conditions such as scale or purpose. Check the original license for the terms of use.

File size and estimated memory per quantization

Up to 8 GB
Up to 16 GB
Up to 24 GB
Up to 48 GB
Up to 128 GB
More

File sizes are the actual values on Hugging Face. Memory is estimated for each context length (KV cache f16). The formula is in How memory is calculated.

All memory figures are Estimated (KV cache f16). It should run on a setup with at least this much VRAM (or Mac unified memory). Click a value to see the devices and models that fit that amount (Find by GPU / Mac).

About the "quality guide" (how far a quantization drifts from the original)

For each quantization type, how far the output drifts from the original model, grouped into six levels from values llama.cpp measured on Llama-3-8B.

The value is mean KLD (the difference between the original and quantized model in next-token probabilities); smaller means closer to the original. Quantizations made with an imatrix (importance data) come out slightly smaller. Levels use the value without an imatrix (or with one, for types that only have that).

These values were not measured on this model. Larger models and MoE models tend to drift less with the same type. Distributor-specific mixed types (such as UD-Q4_K_XL) cannot be matched by type name alone, so they show "-".

Quantization	Quality guide	KLD (no imatrix)	KLD (imatrix)	Size (Llama-3-8B)
Q8_0	Nearly identical	0.0014	-	7.96 GiB
Q6_K	Very small	0.0055	-	6.14 GiB
Q5_K_M	Very small	0.0108	-	5.33 GiB
Q5_K_S	Small	0.0166	-	5.21 GiB
Q5_1	Small	0.0180	-	5.65 GiB
Q5_0	Small	0.0222	-	5.21 GiB
Q4_K_M	Small	0.0313	0.0282	4.58 GiB
Q4_K_S	Medium	0.0431	0.0320	4.37 GiB
IQ4_NL	Small	-	0.0357	4.35 GiB
IQ4_XS	Small	-	0.0363	4.14 GiB
Q4_1	Medium	0.0717	-	4.78 GiB
Q4_0	Medium	0.0719	-	4.34 GiB
Q3_K_L	Medium	0.0872	0.0731	4.03 GiB
Q3_K_M	Medium	0.1019	0.0844	3.74 GiB
IQ3_M	Medium	-	0.1025	3.53 GiB
IQ3_S	Medium	-	0.1113	3.42 GiB
IQ3_XS	Large	-	0.1387	3.28 GiB
IQ3_XXS	Large	-	0.1836	3.05 GiB
Q3_K_S	Large	0.2282	0.1998	3.41 GiB
IQ2_M	Large	-	0.3260	2.74 GiB
Q2_K	Very large	0.4451	0.3322	2.96 GiB
Q2_K_S	Very large	-	0.4034	2.96 GiB
IQ2_S	Very large	-	0.4392	2.56 GiB
IQ2_XS	Very large	-	0.5463	2.43 GiB
IQ2_XXS	Very large	-	0.8120	2.24 GiB
IQ1_M	Very large	-	1.3931	2.01 GiB
IQ1_S	Very large	-	2.2546	1.88 GiB

Source: llama.cpp (MIT), measured on Llama-3-8B against FP16, Wikitext-2, revision f364eb6f. Original table · Reading and choosing quantizations

GGUF source

ivanfioravanti/Qwen3.8-Flash-Next-DS4-Q4

Published by the original developer About this label

Last checked: Oct 9, 2026

Architecture: qwen4-exp-ple; Not supported by mainline llama.cpp (as of b12025)
Parameters: 51.2B
License: qwen-community-1.0 Conditional

File size and memory per quantization for Qwen3.8-Flash-Next-DS4-Q4 (ivanfioravanti/Qwen3.8-Flash-Next-DS4-Q4)
Quantization	File size Measured	Quality guide	4,096	8,192	16,384	32,768	65,536	131,072	262,144
Q4_1	32.0 GB	Medium	33.3 GB	33.4 GB	33.6 GB	34.1 GB	35.0 GB	36.8 GB	40.4 GB

This GGUF format (qwen4-exp-ple) does not exist in mainline llama.cpp (as of b12025). Ollama, LM Studio and mainline llama.cpp cannot load it; use the dedicated tool described by the source.

License and commercial use

Qwen Community License 1.0 Conditional

Allows commercial use. However, companies (including affiliates) that offer the model to third parties as a service (Model as a Service, e.g. via an API) or run an AI assistant business for coding or office work need a separate license from Qwen before commercial use (internal-only use is excluded). Products with over 100 million monthly active users or over USD 20 million in monthly revenue must display the model name.

Based on the license on the original model's Hugging Face page. Original license text (checked Oct 18, 2026)

The summary states facts this site read from the original text and is not legal advice. Always check the original license and its latest terms before use. All licenses

Frequently asked questions

How much memory do I need to run Qwen3.8-Flash-Next-DS4-Q4 (Q4_1)?: The file size is 32.0 GB (measured). With a 8,192-token context, the estimated memory including the KV cache is 33.4 GB. The formula is published at https://localllm.az-arte.com/en/guide/memory-calculation.
Can Qwen3.8-Flash-Next-DS4-Q4 be used commercially?: The original model's license is Qwen Community License 1.0 (Commercial use with conditions).Allows commercial use. However, companies (including affiliates) that offer the model to third parties as a service (Model as a Service, e.g. via an API) or run an AI assistant business for coding or office work need a separate license from Qwen before commercial use (internal-only use is excluded). Products with over 100 million monthly active users or over USD 20 million in monthly revenue must display the model name. Check the original license text before deciding.
Does Qwen3.8-Flash-Next-DS4-Q4 run in 8 GB, 12 GB, 16 GB or 24 GB of VRAM?: 8 GB: no quantization fits; 12 GB: no quantization fits; 16 GB: no quantization fits; 24 GB: no quantization fits (estimated at 8,192 tokens with an f16 KV cache, files from the most-downloaded source).