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KAIROS MM Qwen2.5 VL SFT GGUF

> KAIROS-MM-Qwen2.5-VL-7B-SFT is a multimodal reasoning model based on Qwen2.5-VL, designed to enable robots and vision AI agents to reason about the real world using physics understanding, prior knowledge, and...

TypeOtherModèle de baseprithivMLmods/KAIROS-MM-Qwen2.5-VL-7B-SFTVersionRevision efb6948BClasse

Source du modèle

Type
Other
Taille du fichier
816 MB–14,2 GB
Modèle de base
prithivMLmods/KAIROS-MM-Qwen2.5-VL-7B-SFT
Version
vRevision efb6948
Mis à jour
24 oct. 2026
Téléchargements
179
Source
Hugging Face

Description de la source

KAIROS-MM-Qwen2.5-VL-SFT-GGUF

KAIROS-MM-Qwen2.5-VL-7B-SFT is a multimodal reasoning model based on Qwen2.5-VL, designed to enable robots and vision AI agents to reason about the real world using physics understanding, prior knowledge, and common sense. The model understands space, time, and fundamental physical principles, and is well suited for planning, decision making, and long horizon video reasoning in embodied and agentic systems. It serves as a planning and reasoning backbone for embodied agents, allowing them to infer what actions to take next based on visual observations, temporal context, and physical constraints.

KAIROS-MM-Qwen2.5-VL-SFT [GGUF]

File NameQuant TypeFile SizeFile Link
KAIROS-MM-Qwen2.5-VL-SFT.BF16.ggufBF1615.2 GBDownload
KAIROS-MM-Qwen2.5-VL-SFT.F16.ggufF1615.2 GBDownload
KAIROS-MM-Qwen2.5-VL-SFT.Q8_0.ggufQ8_08.1 GBDownload
KAIROS-MM-Qwen2.5-VL-SFT.mmproj-bf16.ggufmmproj-bf161.36 GBDownload
KAIROS-MM-Qwen2.5-VL-SFT.mmproj-f16.ggufmmproj-f161.36 GBDownload
KAIROS-MM-Qwen2.5-VL-SFT.mmproj-q8_0.ggufmmproj-q8_0856 MBDownload

Quants Usage

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png

Sources

1 source
Hugging FacePrincipalVersion efb694828ccd25807f9edcb6d6c8684c35f61a06
huggingface.co/prithivMLmods/KAIROS-MM-Qwen2.5-VL-SFT-GGUF/tree/efb694828ccd25807f9edcb6d6c8684c35f61a06

Vérifié 24 oct.

Artefacts du modèle

6 artefacts

KAIROS-MM-Qwen2.5-VL-SFT.BF16.gguf

gguf · 14,2 GB · SHA-256 3879f4cf2499…b2ab · Hugging Face

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KAIROS-MM-Qwen2.5-VL-SFT.F16.gguf

gguf · 14,2 GB · SHA-256 a723e6729cd6…b4ff · Hugging Face

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KAIROS-MM-Qwen2.5-VL-SFT.mmproj-bf16.gguf

gguf · 1,26 GB · SHA-256 ea20c556d6e7…b84c · Hugging Face

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KAIROS-MM-Qwen2.5-VL-SFT.mmproj-f16.gguf

gguf · 1,26 GB · SHA-256 ea20c556d6e7…b84c · Hugging Face

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KAIROS-MM-Qwen2.5-VL-SFT.mmproj-q8_0.gguf

gguf · 816 MB · SHA-256 127ff2296619…4842 · Hugging Face

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KAIROS-MM-Qwen2.5-VL-SFT.Q8_0.gguf

gguf · 7,54 GB · SHA-256 c79156643681…18d8 · Hugging Face

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Extraits de sources

3 extraits

--- license: apache-2.0 language: - en base_model: - prithivMLmods/KAIROS-MM-Qwen2.5-VL-7B-SFT pipeline_tag: video-text-to-text library_name: transformers tags: - text-generation-inference - llama.cpp --- # **KAIROS-MM-Qwen2.5-VL-SFT-GGUF** > KAIROS-MM-Qwen2.5-VL-7B-SFT is a multimodal reasoning model based on Qwen2.5-VL, designed to enable robots and vision AI agents to reason about the real world using physics understanding, prior knowledge, and common sense. The model understands space, time, and fundamental physical principles, and is well suited for planning, decision making, and long horizon video reasoning in embodied and agentic systems. It serves as a planning and reasoning backbone for embodied agents, allowing them to infer what actions to take next based on visual observations, temporal context, and physical constraints. ## KAIROS-MM-Qwen2.5-VL-SFT [GGUF] | File Name | Quant Type | File Size | File Link | | - | - | - | - | | KAIROS-MM-Qwen2.5-VL-SFT.BF16.gguf | BF16 | 15.2 GB | [Download](https://huggingface.co/prithivMLmods/KAIROS-MM-Qwen2.5-VL-SFT-GGUF/blob/main/KAIROS-MM-Qwen2.5-VL-SFT.BF16.gguf) | | KAIROS-MM-Qwen2.5-VL-SFT.F16.gguf | F16 | 15.2 GB | [Download](https://huggingface.co/prithivMLmods/KAIROS-MM-Qwen2.5-VL-SFT-GGUF/blob/main/KAIROS-MM-Qwen2.5-VL-SFT.F16.gguf) | | KAIROS-MM-Qwen2.5-VL-SFT.Q8_0.gguf | Q8_0 | 8.1 GB | [Download](https://huggingface.co/prithivMLmods/KAIROS-MM-Qwen2.5-VL-SFT-GGUF/blob/main/KAIROS-MM-Qwen2.5-VL-SFT.Q8_0.gguf) | | KAIROS-MM-Qwen2.5-VL-SFT.mmproj-bf16.gguf | mmproj-bf16 | 1.36 GB | [Download](https://huggingface.co/prithivMLmods/KAIROS-MM-Qwen2.5-VL-SFT-GGUF/blob/main/KAIROS-MM-Qwen2.5-VL-SFT.mmproj-bf16.gguf) | | KAIROS-MM-Qwen2.5-VL-SFT.mmproj-f16.gguf | mmproj-f16 | 1.36 GB | [Download](https://huggingface.co/prithivMLmods/KAIROS-MM-Qwen2.5-VL-SFT-GGUF/blob/main/KAIROS-MM-Qwen2.5-VL-SFT.mmproj-f16.gguf) | | KAIROS-MM-Qwen2.5-VL-SFT.mmproj-q8_0.gguf | mmproj-q8_0 | 856 MB | [Download](https://huggingface.co/prithivMLmods/KAIROS-MM-Qwen2.5-VL-SFT-GGUF/blob/main/KAIROS-MM-Qwen2.5-VL-SFT.mmproj-q8_0.gguf) | ## Quants Usage (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

Source context: 179 downloads · 1 likes · Pipeline video-text-to-text · Library transformers · Repo prithivMLmods/KAIROS-MM-Qwen2.5-VL-SFT-GGUF

Source context: 64 downloads · 1 likes · Pipeline video-text-to-text · Library transformers · Repo prithivMLmods/KAIROS-MM-Qwen2.5-VL-SFT-GGUF