fsxedx/llava-1.6-mistral-7b-gguf overview
GGUF Quantized LLaVA 1.6 Mistral 7B Updated quants and projector from PR 5267 https://github.com/ggerganov/llama.cpp/pull/5267 Provided files | Name | Quant me…
Runs locally from ~595.5 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| llava-1.6-mistral-7b.Q6_K.gguf | GGUF | GGUF | 5.53 GB | Download |
| llava-1.6-mistral-7b.Q8_0.gguf | GGUF | GGUF | 7.17 GB | Download |
| llava-v1.6-mistral-7b.Q3_K.gguf | GGUF | GGUF | 3.28 GB | Download |
| llava-v1.6-mistral-7b.Q3_K_M.gguf | GGUF | GGUF | 3.28 GB | Download |
| llava-v1.6-mistral-7b.Q3_K_XS.gguf | GGUF | GGUF | 2.79 GB | Download |
| llava-v1.6-mistral-7b.Q4_K_M.gguf | GGUF | GGUF | 4.07 GB | Download |
| llava-v1.6-mistral-7b.Q5_K_M.gguf | GGUF | GGUF | 4.78 GB | Download |
| llava-v1.6-mistral-7b.Q5_K_S.gguf | GGUF | GGUF | 4.65 GB | Download |
| llava-v1.6-mistral-7b.Q6_K.gguf | GGUF | GGUF | 5.53 GB | Download |
| llava-v1.6-mistral-7b.Q8_0.gguf | GGUF | GGUF | 7.17 GB | Download |
| mmproj-model-f16.gguf | GGUF | F16 | 595.5 MB | Download |
Model Details
| Model ID | fsxedx/llava-1.6-mistral-7b-gguf |
|---|---|
| Author | fsxedx |
| Pipeline | image-text-to-text |
| License | apache-2.0 |
| Base model | — |
| Last modified | 2026-07-24T16:49:15.000Z |
Model README
---
license: apache-2.0
tags:
- llava
pipeline_tag: image-text-to-text
---
GGUF Quantized LLaVA 1.6 Mistral 7B
Updated quants and projector from PR #5267
Provided files
| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| llava-v1.6-mistral-7b.Q3_K_XS.gguf | Q3_K_XS | 3 | 2.99 GB| very small, high quality loss |
| llava-v1.6-mistral-7b.Q3_K_M.gguf | Q3_K_M | 3 | 3.52 GB| very small, high quality loss |
| llava-v1.6-mistral-7b.Q4_K_M.gguf | Q4_K_M | 4 | 4.37 GB| medium, balanced quality - recommended |
| llava-v1.6-mistral-7b.Q5_K_S.gguf | Q5_K_S | 5 | 5.00 GB| large, low quality loss - recommended |
| llava-v1.6-mistral-7b.Q5_K_M.gguf | Q5_K_M | 5 | 5.13 GB| large, very low quality loss - recommended |
| llava-v1.6-mistral-7b.Q6_K.gguf | Q6_K | 6 | 5.94 GB| very large, extremely low quality loss |
| llava-v1.6-mistral-7b.Q8_0.gguf | Q8_0 | 8 | 7.7 GB| very large, extremely low quality loss - not recommended |
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ORIGINAL LLaVA Model Card
Model details
Model type:
LLaVA is an open-source chatbot trained by fine-tuning LLM on multimodal instruction-following data.
It is an auto-regressive language model, based on the transformer architecture.
Base LLM: mistralai/Mistral-7B-Instruct-v0.2
Model date:
LLaVA-v1.6-Mistral-7B was trained in December 2023.
Paper or resources for more information:
https://llava-vl.github.io/
License
mistralai/Mistral-7B-Instruct-v0.2 license.
Where to send questions or comments about the model:
https://github.com/haotian-liu/LLaVA/issues
Intended use
Primary intended uses:
The primary use of LLaVA is research on large multimodal models and chatbots.
Primary intended users:
The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
Training dataset
- 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
- 158K GPT-generated multimodal instruction-following data.
- 500K academic-task-oriented VQA data mixture.
- 50K GPT-4V data mixture.
- 40K ShareGPT data.
Evaluation dataset
A collection of 12 benchmarks, including 5 academic VQA benchmarks and 7 recent benchmarks specifically proposed for instruction-following LMMs.
Run fsxedx/llava-1.6-mistral-7b-gguf with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models