base_model: DavidAU/Qwen3-30B-A1.5B-High-Speed
language:
- en
library_name: transformers
mradermacher:
readme_rev: 1
no_imatrix: >-
failed to quantize: Missing importance matrix for tensor
blk.42.ffn_down_exps.weight in a very low-bit quantization
quantized_by: mradermacher
tags:
- 32 k context
- reasoning
- thinking
- qwen3
- 4 experts activated
- double speed
- 128 experts
About
static quants of https://huggingface.co/DavidAU/Qwen3-30B-A1.5B-High-Speed
For a convenient overview and download list, visit our model page for this model.
Usage
If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.
Provided Quants
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|---|---|---|---|
| GGUF | Q2_K | 11.4 | |
| GGUF | IQ3_XS | 12.7 | |
| GGUF | Q3_K_S | 13.4 | |
| GGUF | IQ3_S | 13.4 | beats Q3_K* |
| GGUF | IQ3_M | 13.6 | |
| GGUF | Q3_K_M | 14.8 | lower quality |
| GGUF | Q3_K_L | 16.0 | |
| GGUF | IQ4_XS | 16.7 | |
| GGUF | Q4_K_S | 17.6 | fast, recommended |
| GGUF | Q4_K_M | 18.7 | fast, recommended |
| GGUF | Q5_K_S | 21.2 | |
| GGUF | Q5_K_M | 21.8 | |
| GGUF | Q6_K | 25.2 | very good quality |
| GGUF | Q8_0 | 32.6 | fast, best quality |
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
FAQ / Model Request
See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.
Thanks
I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.