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SWE Review 30B A3B GGUF

For a convenient overview and download list, visit our model page for this model.

TipoOtherModelo baseLego-X/SWE-Review-30B-A3BVersiónRevision 83c1e93Publicador@mradermacherCcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
10,5–30,3 GB
Modelo base
Lego-X/SWE-Review-30B-A3B
Versión
vRevision 83c1e93
Actualizado
3 oct 2026
Publicador
@mradermacher
Descargas
368
Parámetros
30B
Fuente
Hugging Face

Descripción de la fuente

About

static quants of https://huggingface.co/Lego-X/SWE-Review-30B-A3B

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/SWE-Review-30B-A3B-i1-GGUF

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)

LinkTypeSize/GBNotes
GGUFQ2_K11.4
GGUFQ3_K_S13.4
GGUFQ3_K_M14.8lower quality
GGUFQ3_K_L16.0
GGUFIQ4_XS16.7
GGUFQ4_K_S17.6fast, recommended
GGUFQ4_K_M18.7fast, recommended
GGUFQ5_K_S21.2
GGUFQ5_K_M21.8
GGUFQ6_K25.2very good quality
GGUFQ8_032.6fast, 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.

Fuentes

1 fuente
Hugging FacePrincipalVersión 83c1e93a6995340a5921d54f8586e316368957c1
huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/tree/83c1e93a6995340a5921d54f8586e316368957c1

Verificado 3 oct

Artefactos del modelo

11 artefactos

SWE-Review-30B-A3B.IQ4_XS.gguf

gguf · 15,4 GB · SHA-256 978a191f699c…087d · Hugging Face

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SWE-Review-30B-A3B.Q2_K.gguf

gguf · 10,5 GB · SHA-256 329e044c2745…dfc4 · Hugging Face

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SWE-Review-30B-A3B.Q3_K_L.gguf

gguf · 14,8 GB · SHA-256 765c3865ce07…8aea · Hugging Face

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SWE-Review-30B-A3B.Q3_K_M.gguf

gguf · 13,7 GB · SHA-256 b9b130d08088…4c25 · Hugging Face

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SWE-Review-30B-A3B.Q3_K_S.gguf

gguf · 12,4 GB · SHA-256 3095171232a1…e70b · Hugging Face

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SWE-Review-30B-A3B.Q4_K_M.gguf

gguf · 17,3 GB · SHA-256 6a92f807b7b9…bfab · Hugging Face

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SWE-Review-30B-A3B.Q4_K_S.gguf

gguf · 16,3 GB · SHA-256 c3515e6233b6…f12e · Hugging Face

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SWE-Review-30B-A3B.Q5_K_M.gguf

gguf · 20,2 GB · SHA-256 277488df5513…9b4d · Hugging Face

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SWE-Review-30B-A3B.Q5_K_S.gguf

gguf · 19,6 GB · SHA-256 c1a81db5854c…6a44 · Hugging Face

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SWE-Review-30B-A3B.Q6_K.gguf

gguf · 23,4 GB · SHA-256 7b3463728c81…d093 · Hugging Face

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SWE-Review-30B-A3B.Q8_0.gguf

gguf · 30,3 GB · SHA-256 3cb9c58a3525…2eb8 · Hugging Face

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Extractos de fuentes

3 extractos

--- base_model: Lego-X/SWE-Review-30B-A3B language: - en library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - code-review - software-engineering - swe-bench - agentic - moe --- ## 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/Lego-X/SWE-Review-30B-A3B <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#SWE-Review-30B-A3B-GGUF).*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/SWE-Review-30B-A3B-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](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q2_K.gguf) | Q2_K | 11.4 | | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q3_K_S.gguf) | Q3_K_S | 13.4 | | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q3_K_M.gguf) | Q3_K_M | 14.8 | lower quality | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q3_K_L.gguf) | Q3_K_L | 16.0 | | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.IQ4_XS.gguf) | IQ4_XS | 16.7 | | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q4_K_S.gguf) | Q4_K_S | 17.6 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q4_K_M.gguf) | Q4_K_M | 18.7 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q5_K_S.gguf) | Q5_K...

--- base_model: SWE-Lego/SWE-Review-30B-A3B language: - en library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - code-review - software-engineering - swe-bench - agentic - moe --- ## 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/SWE-Lego/SWE-Review-30B-A3B <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#SWE-Review-30B-A3B-GGUF).*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/SWE-Review-30B-A3B-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](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q2_K.gguf) | Q2_K | 11.4 | | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q3_K_S.gguf) | Q3_K_S | 13.4 | | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q3_K_M.gguf) | Q3_K_M | 14.8 | lower quality | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q3_K_L.gguf) | Q3_K_L | 16.0 | | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.IQ4_XS.gguf) | IQ4_XS | 16.7 | | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q4_K_S.gguf) | Q4_K_S | 17.6 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q4_K_M.gguf) | Q4_K_M | 18.7 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/SWE-Review-30B-A3B-GGUF/resolve/main/SWE-Review-30B-A3B.Q5_K_S.gguf) |...

Source context: 368 downloads · 0 likes · Library transformers · Repo mradermacher/SWE-Review-30B-A3B-GGUF