What are the hardware requirements for Co Instruct Llava V1.5 7B?

Co Instruct Llava V1.5 7B requires approximately 14.1 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Co Instruct Llava V1.5 7B and how large is it?

Co Instruct Llava V1.5 7B is developed by q-future, 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 Co Instruct Llava V1.5 7B?

Co Instruct Llava V1.5 7B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Co Instruct Llava V1.5 7B by q-future — VRAM 14.1GB, 4K context

Name: Co Instruct Llava V1.5 7B
Author: q-future

Co Instruct Llava V1.5 7B is an open-source language model by q-future. Features: 7b LLM, VRAM: 14.1GB, Context: 4K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.11.

Arxiv:2402.16641 Dataset:q-future/co-instruct-d... Endpoints compatible Instruct Llava llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/q-future/co-instruct-llava-v1.5-7b

Co Instruct Llava V1.5 7B Parameters and Internals

Model Type

Facilitator for LLaVA structure

Use Cases

Areas:

Facilitating users who prefer LLaVA structure

Limitations:

Not very friendly to multi-image scenarios

Training Details

Data Sources:

q-future/Co-Instruct-DB

Data Volume:

562K

LLM Name	Co Instruct Llava V1.5 7B
Repository 🤗	https://huggingface.co/q-future/co-instruct-llava-v1.5-7b
Model Size	7b
Required VRAM	14.1 GB
Updated	2026-08-02
Maintainer	q-future
Model Type	llava_llama
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.2 GB: 3-of-3 0.0 GB
Model Architecture	LlavaLlamaForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Co Instruct Llava V1.5 7B 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 Co Instruct Llava V1.5 7B

Best Alternatives	Context / RAM	Downloads	Likes
Llava V1.6 Mistral 7B PATCHED	32K / 15.1 GB	17	8
Table Llava V1.5 7B	4K / 14.2 GB	9	13
Quilt Llava V1.5 7B	4K / 14.2 GB	610	9
...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 q-future/co-instruct-llava-v1.5-7b.