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K2-Horizon-MoVA-36B-A4B

K2-Horizon-MoVA-36B-A4B is a high-efficiency Mixture-of-Experts (MoE) model designed to bridge the gap between mid-sized parameter counts and high-performance reasoning. By utilizing a 36B architecture with an active parameter count of approximately 4B, it offers a highly optimized compute-to-performance ratio. For developers, this means you can achieve sophisticated text generation and logical reasoning capabilities without the massive VRAM overhead typically required by dense 30B+ models. It is particularly well-suited for deployment in resource-constrained environments or edge-cloud hybrid setups where low latency and high throughput are critical. Built under the Apache 2.0 license, it provides a flexible foundation for fine-tuning on domain-specific datasets or integrating into RAG (Retrieval-Augmented Generation) pipelines. Compared to standard dense models, the MoE architecture allows for faster inference speeds, making it a strong candidate for real-time conversational agents and automated content workflows.

IFMtext generation
01 / MODEL CARD

Model card

K2-Horizon-MoVA-36B-A4B is a high-efficiency Mixture-of-Experts (MoE) model designed to bridge the gap between mid-sized parameter counts and high-performance reasoning. By utilizing a 36B architecture with an active parameter count of approximately 4B, it offers a highly optimized compute-to-performance ratio. For developers, this means you can achieve sophisticated text generation and logical reasoning capabilities without the massive VRAM overhead typically required by dense 30B+ models. It is particularly well-suited for deployment in resource-constrained environments or edge-cloud hybrid setups where low latency and high throughput are critical. Built under the Apache 2.0 license, it provides a flexible foundation for fine-tuning on domain-specific datasets or integrating into RAG (Retrieval-Augmented Generation) pipelines. Compared to standard dense models, the MoE architecture allows for faster inference speeds, making it a strong candidate for real-time conversational agents and automated content workflows.

Model typetext generation
ProviderIFM
Licenseapache-2.0
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/IFM/K2-Horizon-MoVA-36B-A4B
View model source
Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: IFM/K2-Horizon-MoVA-36B-A4B
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model IFM/K2-Horizon-MoVA-36B-A4B
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model IFM/K2-Horizon-MoVA-36B-A4B README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('IFM/K2-Horizon-MoVA-36B-A4B')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/IFM/K2-Horizon-MoVA-36B-A4B.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/IFM/K2-Horizon-MoVA-36B-A4B.git
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

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