What are the hardware requirements for Imagine V9?

Imagine V9 requires approximately 0.9 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Imagine V9 and how large is it?

Imagine V9 is developed by Interchained, a model with 1.3b 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 Imagine V9?

Imagine V9 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Imagine V9 by Interchained — VRAM 0.9GB, 16K context

Name: Imagine V9
Author: Interchained

Imagine V9 is an open-source language model by Interchained. Features: 1.3b LLM, VRAM: 0.9GB, Context: 16K, License: apache-2.0, Quantized, LLM Explorer Score: 0.32.

Base model:interchained/imagin... Base model:quantized:interchai... Code-generation Codegen Conversational En Endpoints compatible Gguf Llama Postgresql Q4 Quantized Region:us Safetensors Sql

Model Card on HF 🤗: https://huggingface.co/Interchained/imagine-v9

Imagine V9 Parameters and Internals

LLM Name	Imagine V9
Repository 🤗	https://huggingface.co/Interchained/imagine-v9
Base Model(s)	Imagine V8 Interchained/imagine-v8
Model Size	1.3b
Required VRAM	0.9 GB
Updated	2026-10-10
Maintainer	Interchained
Model Type	llama
Model Files	0.9 GB 2.7 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	q4\|gguf\|q4_k
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	16384
Model Max Length	16384
Transformers Version	5.19.0
Tokenizer Class	TokenizersBackend
Padding Token	<｜end▁of▁sentence｜>
Vocabulary Size	32256

Rank the Imagine V9 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

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