simpledirect/Vinci-Bozza-1.0-GGUF overview
<img src="./assets/vinci vero header.svg" alt="Vinci with Vero, its character" width="280" height="64" Vinci Bozza 1.0 — GGUF GGUF quantizations of simpledirec…
Runs locally from ~5.24 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | simpledirect/Vinci-Bozza-1.0-GGUF |
|---|---|
| Author | simpledirect |
| Pipeline | text-generation |
| License | apache-2.0 |
| Base model | simpledirect/Vinci-Bozza-1.0 |
| Last modified | 2026-09-28T03:30:23.000Z |
Model README
---
base_model: simpledirect/Vinci-Bozza-1.0
pipeline_tag: text-generation
tags:
- gguf
- quantized
- qwen3_5
- conversational
- chat
- character
- constitutional-ai
- simpledirect
- vinci
license: apache-2.0
---
<img src="./assets/vinci-vero-header.svg" alt="Vinci with Vero, its character" width="280" height="64">
Vinci Bozza 1.0 — GGUF
GGUF quantizations of simpledirect/Vinci-Bozza-1.0 for local inference with Ollama, LM Studio, and llama.cpp.
Text-only. The source model is multimodal (image-text-to-text); these GGUF conversions include the language model only — no mmproj / vision projector. For image input, use the safetensors build: simpledirect/Vinci-Bozza-1.0.
These files are not the measured artifact
🔴 No GGUF file in this repository has been evaluated. The benchmark figures on the full-precision card were measured on the unquantized bf16 weights, not on any file here. Quantization shifts scores, 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. The file sizes and memory figures below are measured, and describe storage and memory cost only. A file's presence in this repository is not a performance claim about that tier, and not a claim of parity with the full-precision weights.
Variants
| File | Size | Notes |
|---|---|---|
| Vinci-Bozza-1.0-Q6_K.gguf | ~6.8 GB | 6-bit K-quant |
| Vinci-Bozza-1.0-Q5_K_M.gguf | ~6.0 GB | 5-bit K-quant, medium mixture |
| Vinci-Bozza-1.0-Q4_K_M.gguf | ~5.2 GB | 4-bit K-quant, medium mixture |
Quick start
# Ollama — default quant auto-selected
ollama run hf.co/simpledirect/Vinci-Bozza-1.0-GGUF
# Specific quant
ollama run hf.co/simpledirect/Vinci-Bozza-1.0-GGUF:Q5_K_M
llama.cpp:
llama-cli -m Vinci-Bozza-1.0-Q5_K_M.gguf --chat-template chatml -p "Hello, who are you?"
Hardware requirements
| Variant | GPU VRAM | System RAM (CPU-only) |
|---|---|---|
| Q6_K | 10 GB | 16 GB |
| Q5_K_M | 8 GB | 14 GB |
| Q4_K_M | 7 GB | 12 GB |
Mac M-series: Q5_K_M runs comfortably on 16 GB unified memory; Q6_K needs 24 GB.
Prompt format
Uses Qwen / ChatML chat template. Pass enable_thinking=False (or equivalent) to suppress <think> blocks for normal chat use.
Links
- Full model (safetensors, BF16): simpledirect/Vinci-Bozza-1.0
- GitHub: https://github.com/getsimpledirect
- The Constitution: https://guide.getsimpledirect.com/constitution
Run simpledirect/Vinci-Bozza-1.0-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models