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simpledirect/Vinci-Prova-7B-1.0-GGUF overview

<img src="./assets/vinci vero header.svg" alt="Vinci with Vero, its character" width="280" height="64" Vinci Prova 7B 1.0 GGUF Quantised GGUF builds of simpled…

ggufquantizedvinciprovabase_model:simpledirect/Vinci-Prova-7B-1.0base_model:quantized:simpledirect/Vinci-Prova-7B-1.0license:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~4.07 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
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Repository Files & Downloads

4 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Vinci-Prova-7B-1.0-Q4_K_M.ggufGGUFQ4_K_M4.07 GBDownload
Vinci-Prova-7B-1.0-Q5_K_M.ggufGGUFQ5_K_M4.78 GBDownload
Vinci-Prova-7B-1.0-Q8_0.ggufGGUFQ8_07.17 GBDownload
Vinci-Prova-7B-1.0-f16.ggufGGUFF1613.50 GBDownload

Model Details

Model IDsimpledirect/Vinci-Prova-7B-1.0-GGUF
Authorsimpledirect
Pipeline—
Licenseapache-2.0
Base modelsimpledirect/Vinci-Prova-7B-1.0
Last modified2026-09-28T03:30:58.000Z

Model README

---

license: apache-2.0

base_model: simpledirect/Vinci-Prova-7B-1.0

tags:

- gguf

- quantized

- vinci

- prova

---

<img src="./assets/vinci-vero-header.svg" alt="Vinci with Vero, its character" width="280" height="64">

Vinci Prova 7B 1.0 - GGUF

Quantised GGUF builds of

simpledirect/Vinci-Prova-7B-1.0.

| file | quantisation | sha256 |

|---|---|---|

| Vinci-Prova-7B-1.0-f16.gguf | f16 (unquantised conversion) | 195460f2f2fbf033f5bee226903a9ab51591d26f62f6cd83702867e5d66f9e03 |

| Vinci-Prova-7B-1.0-Q4_K_M.gguf | Q4_K_M | 655886167ea8f07877954ee949b205557eb810774860535b84aa41c3446ca750 |

| Vinci-Prova-7B-1.0-Q5_K_M.gguf | Q5_K_M | ed521b15992b6716042e6bae4a9785bd1827ec05bf99661473adeb035c830f1b |

| Vinci-Prova-7B-1.0-Q8_0.gguf | Q8_0 | b0b724b4dd77d132f47ed364fed7053fc0dfa30edb4839cc07212ec0f206b9dc |

Verify what you downloaded against these hashes. Equal file size is not identity.

These files are not the measured artifact

🔴 No GGUF file in this repository has been evaluated. Every published measurement was taken on the unquantised weights in the main repo, not on any file here. Quantisation changes model behaviour, and with no per-tier measurement this card cannot say in which direction or by how much for any tier.

This card therefore publishes no per-tier score, no quality ranking between the tiers, and no recommended tier. A file's presence in this repository is not a performance claim about that tier, and not a claim of parity with the unquantised weights.

All evaluation results, limitations, intended use and provenance live on the main repo.

Read its model card before using these builds. Nothing is restated here, so there is one

place for a number to be correct. The full study is published as

Vinci Technical Report No. 1 (CC BY 4.0).

Follow-up, 1 September 2026. Technical Report No. 2

applied the same frozen recipe to three model families and did not establish general

cross-lineage portability. The Report No. 1 measurements are unchanged. Both reports are

summarised on the main repo's card; nothing is restated here.

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