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...
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 Name | Quant Type | File Size | File Link |
|---|---|---|---|
| KAIROS-MM-Qwen2.5-VL-SFT.BF16.gguf | BF16 | 15.2 GB | Download |
| KAIROS-MM-Qwen2.5-VL-SFT.F16.gguf | F16 | 15.2 GB | Download |
| KAIROS-MM-Qwen2.5-VL-SFT.Q8_0.gguf | Q8_0 | 8.1 GB | Download |
| KAIROS-MM-Qwen2.5-VL-SFT.mmproj-bf16.gguf | mmproj-bf16 | 1.36 GB | Download |
| KAIROS-MM-Qwen2.5-VL-SFT.mmproj-f16.gguf | mmproj-f16 | 1.36 GB | Download |
| KAIROS-MM-Qwen2.5-VL-SFT.mmproj-q8_0.gguf | mmproj-q8_0 | 856 MB | Download |
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
Sources
1 sourceVérifié 24 oct.
Artefacts du modèle
6 artefacts
Artefacts du modèle
6 artefactsKAIROS-MM-Qwen2.5-VL-SFT.BF16.gguf
gguf · 14,2 GB · SHA-256 3879f4cf2499…b2ab · Hugging Face
TéléchargerKAIROS-MM-Qwen2.5-VL-SFT.F16.gguf
gguf · 14,2 GB · SHA-256 a723e6729cd6…b4ff · Hugging Face
TéléchargerKAIROS-MM-Qwen2.5-VL-SFT.mmproj-bf16.gguf
gguf · 1,26 GB · SHA-256 ea20c556d6e7…b84c · Hugging Face
TéléchargerKAIROS-MM-Qwen2.5-VL-SFT.mmproj-f16.gguf
gguf · 1,26 GB · SHA-256 ea20c556d6e7…b84c · Hugging Face
TéléchargerKAIROS-MM-Qwen2.5-VL-SFT.mmproj-q8_0.gguf
gguf · 816 MB · SHA-256 127ff2296619…4842 · Hugging Face
TéléchargerKAIROS-MM-Qwen2.5-VL-SFT.Q8_0.gguf
gguf · 7,54 GB · SHA-256 c79156643681…18d8 · Hugging Face
TéléchargerExtraits de sources
3 extraits
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): 
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
