What are the hardware requirements for Llava V1.6 Mistral 7B PATCHED?

Llava V1.6 Mistral 7B PATCHED requires approximately 15.1 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llava V1.6 Mistral 7B PATCHED and how large is it?

Llava V1.6 Mistral 7B PATCHED is developed by Trelis, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Llava V1.6 Mistral 7B PATCHED?

Llava V1.6 Mistral 7B PATCHED is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llava V1.6 Mistral 7B PATCHED by Trelis — VRAM 15.1GB, 32K context

Name: Llava V1.6 Mistral 7B PATCHED
Author: Trelis

Llava V1.6 Mistral 7B PATCHED is an open-source language model by Trelis. Features: 7b LLM, VRAM: 15.1GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.11.

Conversational Image-text-to-text Instruct Llava Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Trelis/llava-v1.6-mistral-7b-PATCHED

Llava V1.6 Mistral 7B PATCHED Parameters and Internals

Model Type

text generation, multimodal

Use Cases

Primary Use Cases:

Research on large multimodal models and chatbots.

Additional Notes

Patched version with patches from aliencaocao applied.

Training Details

Data Sources:

558K filtered image-text pairs from LAION/CC/SBU, 158K GPT-generated multimodal instruction-following data, 500K academic-task-oriented VQA data mixture, 50K GPT-4V data mixture, 40K ShareGPT data

Model Architecture:

Transformer architecture

LLM Name	Llava V1.6 Mistral 7B PATCHED
Repository 🤗	https://huggingface.co/Trelis/llava-v1.6-mistral-7b-PATCHED
Model Size	7b
Required VRAM	15.1 GB
Updated	2026-07-30
Maintainer	Trelis
Model Type	llava
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 0.3 GB: 4-of-4
Model Architecture	LlavaLlamaForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	<pad>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Llava V1.6 Mistral 7B PATCHED capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Llava V1.6 Mistral 7B PATCHED

Best Alternatives	Context / RAM	Downloads	Likes
Table Llava V1.5 7B	4K / 14.2 GB	9	13
Quilt Llava V1.5 7B	4K / 14.2 GB	610	9
Co Instruct Llava V1.5 7B	4K / 14.1 GB	6	1
...ct4V LLaVA Instruct Mix880k 7B	4K / 14.2 GB	7	3
...V1.5 7b Qinstruct Preview V0.1	4K / 14.2 GB	76	5
Chinese LLaVA Baichuan	2K / 28 GB	7	9
KoLLaVA KoVicuna 7B	2K / 27 GB	14	13
Llava 1.6 Gptq 8bit	32K / 9.6 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than Trelis/llava-v1.6-mistral-7b-PATCHED.