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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…

transformersggufendataset:nvidia/When2Calldataset:Salesforce/xlam-function-calling-60kdataset:glaiveai/glaive-function-calling-v2dataset:Team-ACE/ToolACEdataset:Agent-Ark/Toucan-1.5Mdataset:Nanbeige/ToolMinddataset:nvidia/Nemotron-SFT-Agentic-v2dataset:Jackrong/GLM-5.1-Reasoning-1M-Cleanedbase_model:BSC-LT/ALIA-40b-fc-2606base_model:quantized:BSC-LT/ALIA-40b-fc-2606license:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~14.63 GB disk (16 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

11 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
ALIA-40b-fc-2606.IQ4_XS.ggufGGUFGGUF20.81 GBDownload
ALIA-40b-fc-2606.Q2_K.ggufGGUFGGUF14.63 GBDownload
ALIA-40b-fc-2606.Q3_K_L.ggufGGUFGGUF20.14 GBDownload
ALIA-40b-fc-2606.Q3_K_M.ggufGGUFGGUF18.67 GBDownload
ALIA-40b-fc-2606.Q3_K_S.ggufGGUFGGUF16.95 GBDownload
ALIA-40b-fc-2606.Q4_K_M.ggufGGUFGGUF22.90 GBDownload
ALIA-40b-fc-2606.Q4_K_S.ggufGGUFGGUF21.84 GBDownload
ALIA-40b-fc-2606.Q5_K_M.ggufGGUFGGUF26.78 GBDownload
ALIA-40b-fc-2606.Q5_K_S.ggufGGUFGGUF26.16 GBDownload
ALIA-40b-fc-2606.Q6_K.ggufGGUFGGUF30.90 GBDownload
ALIA-40b-fc-2606.Q8_0.ggufGGUFGGUF40.02 GBDownload

Model Details

Model IDmradermacher/ALIA-40b-fc-2606-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelBSC-LT/ALIA-40b-fc-2606
Last modified2026-07-03T20:55:55.000Z

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):

!image.png

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 -->

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