mradermacher/ALIA-40b-fc-2606-GGUF overview
About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: < quants: x f16 Q4 K S Q2 K Q8 0 Q6 K Q3 K M Q3 K S Q3 K L Q4…
Runs locally from ~14.63 GB disk (16 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| ALIA-40b-fc-2606.IQ4_XS.gguf | GGUF | GGUF | 20.81 GB | Download |
| ALIA-40b-fc-2606.Q2_K.gguf | GGUF | GGUF | 14.63 GB | Download |
| ALIA-40b-fc-2606.Q3_K_L.gguf | GGUF | GGUF | 20.14 GB | Download |
| ALIA-40b-fc-2606.Q3_K_M.gguf | GGUF | GGUF | 18.67 GB | Download |
| ALIA-40b-fc-2606.Q3_K_S.gguf | GGUF | GGUF | 16.95 GB | Download |
| ALIA-40b-fc-2606.Q4_K_M.gguf | GGUF | GGUF | 22.90 GB | Download |
| ALIA-40b-fc-2606.Q4_K_S.gguf | GGUF | GGUF | 21.84 GB | Download |
| ALIA-40b-fc-2606.Q5_K_M.gguf | GGUF | GGUF | 26.78 GB | Download |
| ALIA-40b-fc-2606.Q5_K_S.gguf | GGUF | GGUF | 26.16 GB | Download |
| ALIA-40b-fc-2606.Q6_K.gguf | GGUF | GGUF | 30.90 GB | Download |
| ALIA-40b-fc-2606.Q8_0.gguf | GGUF | GGUF | 40.02 GB | Download |
Model Details
| Model ID | mradermacher/ALIA-40b-fc-2606-GGUF |
|---|---|
| Author | mradermacher |
| Pipeline | — |
| License | apache-2.0 |
| Base model | BSC-LT/ALIA-40b-fc-2606 |
| Last modified | 2026-07-03T20:55:55.000Z |
Model README
---
base_model: BSC-LT/ALIA-40b-fc-2606
datasets:
- nvidia/When2Call
- Salesforce/xlam-function-calling-60k
- glaiveai/glaive-function-calling-v2
- Team-ACE/ToolACE
- Agent-Ark/Toucan-1.5M
- Nanbeige/ToolMind
- nvidia/Nemotron-SFT-Agentic-v2
- Jackrong/GLM-5.1-Reasoning-1M-Cleaned
language:
- en
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
---
About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static quants of https://huggingface.co/BSC-LT/ALIA-40b-fc-2606
<!-- provided-files -->
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/ALIA-40b-fc-2606-i1-GGUF
Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) 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 | 15.8 | |
| GGUF | Q3_K_S | 18.3 | |
| GGUF | Q3_K_M | 20.1 | lower quality |
| GGUF | Q3_K_L | 21.7 | |
| GGUF | IQ4_XS | 22.4 | |
| GGUF | Q4_K_S | 23.5 | fast, recommended |
| GGUF | Q4_K_M | 24.7 | fast, recommended |
| GGUF | Q5_K_S | 28.2 | |
| GGUF | Q5_K_M | 28.9 | |
| GGUF | Q6_K | 33.3 | very good quality |
| GGUF | Q8_0 | 43.1 | 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.
<!-- end -->
Run mradermacher/ALIA-40b-fc-2606-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models