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  • Devstral-Small-2507-MLX-6bit↗

    lmstudio-community

    *👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. **Model creator**: mistralai **Original model**: Devstral-Small-2507 **MLX quantization**: provided by LM Studio team using mlx_lm **LM Studio model page**: mistralai/devstral-small-2507 LM Studio is not the creator, originator, or owner of any Model featured in the Community Model Program. Each Community Model is created and provided by third parties. LM Studio does not endorse, support, represent or guarantee the completeness, truthfulness, accuracy, or reliability of any Community Model. You understand that Community Models can produce content that might be offensive, harmful, inaccurate or otherwise inappropriate, or deceptive. Each Community Model is the sole responsibility of the person or entity who originated such Model. LM Studio may not monitor or control the Community Models and cannot, and does not, take responsibility for any such Model. LM Studio disclaims all warranties or guarantees about the accuracy, reliability or benefits of the Community Models. LM Studio further disclaims any warranty that the Community Model will meet your requirements, be secure, uninterrupted or available at any time or location, or error-free, viruses-free, or that any errors will be corrected, or otherwise. You will be solely responsible for any damage resulting from your use of or access to the Community Models, your downloading of any Community Model, or use of any other Community Model provided by or through LM Studio.

  • Magistral-Small-2509-MLX-4bit↗

    lmstudio-community

    _👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord_. **Model creator**: mistralai **Original model**: Magistral-Small-2509 **MLX quantization**: provided by LM Studio team using mlx_vlm LM Studio is not the creator, originator, or owner of any Model featured in the Community Model Program. Each Community Model is created and provided by third parties. LM Studio does not endorse, support, represent or guarantee the completeness, truthfulness, accuracy, or reliability of any Community Model. You understand that Community Models can produce content that might be offensive, harmful, inaccurate or otherwise inappropriate, or deceptive. Each Community Model is the sole responsibility of the person or entity who originated such Model. LM Studio may not monitor or control the Community Models and cannot, and does not, take responsibility for any such Model. LM Studio disclaims all warranties or guarantees about the accuracy, reliability or benefits of the Community Models. LM Studio further disclaims any warranty that the Community Model will meet your requirements, be secure, uninterrupted or available at any time or location, or error-free, viruses-free, or that any errors will be corrected, or otherwise. You will be solely responsible for any damage resulting from your use of or access to the Community Models, your downloading of any Community Model, or use of any other Community Model provided by or through LM Studio.

  • SmolVLM-Instruct↗

    HuggingFaceTB

    SmolVLM is a compact open multimodal model that accepts arbitrary sequences of image and text inputs to produce text outputs. Designed for efficiency, SmolVLM can answer questions about images, describe visual content, create stories grounded on multiple images, or function as a pure language model without visual inputs. Its lightweight architecture makes it suitable for on-device applications while maintaining strong performance on multimodal tasks. SmolVLM can be used for inference on multimodal (image + text) tasks where the input comprises text queries along with one or more images. Text and images can be interleaved arbitrarily, enabling tasks like image captioning, visual question answering, and storytelling based on visual content. The model does not support image generation. SmolVLM leverages the lightweight SmolLM2 language model to provide a compact yet powerful multimodal experience. It introduces several changes compared to previous Idefics models:

  • DeepSeek-R1-0528-Qwen3-8B-GGUF↗

    lmstudio-community

    *👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. **Model creator:** deepseek-ai **Original model**: DeepSeek-R1-0528-Qwen3-8B **GGUF quantization:** provided by bartowski based on `llama.cpp` release b5524 **LM Studio Model Page:** https://lmstudio.ai/models/deepseek/deepseek-r1-0528-qwen3-8b Created by distilling the chain-of-thought from DeepSeek-R1-0528 to post-train Qwen3 8B Base

  • MixedQuantFlux↗

    ChrisGoringe

    *Note that all these models are derivatives of black-forest-labs/FLUX.1-dev and therefore covered by the [FLUX.1 [dev] Non-Commercial License](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md) license.* A collection of GGUF models using mixed quantization (different layers quantized to different precision to optimise fidelity v. memory), created using mixed gguf converter. They can be loaded in ComfyUI using the ComfyUI GGUF Nodes. Just put the gguf files in your models/unet directory.

  • Huihui-Qwen3.8-27B-abliterated-GGUF↗

    xrachelburns

    This is an uncensored version of Qwen/Qwen3.8-27B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. The newly added **Huihui-Qwen3.8-27B-abliterated-Swift** series come from ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF. Only layers **22 to 52 (0-based indexing)** have been ablated, while the other layers remain unablated. It may come with a small disclaimer warning. This is just a test/validation. The newly added **Huihui-Qwen3.8-27B-abliterated-Ternary** series come from prism-ml/Ternary-Bonsai-2-27B-gguf. Only layers **22 to 52 (0-based indexing)** have been ablated, while the other layers remain unablated. It may come with a small disclaimer warning. The size after conversion may differ from the original GGUF (Some of the weights are converted from PTQ1 to Q2_K or Q3_K.). This is just a test/validation.

  • LTX_2.3_Fantasy_Realism_Style_LoRa↗

    vrgamedevgirl84

    This LoRA creates a **cinematic fantasy realism live-action film** look. **The dataset used to create this LoRA did not use any IP.** It is a **grounded high-fantasy cinematic style**, not actual stills or images from any movies or TV shows. The workflow used to create the sample videos can be found HERE. All sample videos are **text-to-video**, not image-to-video. Characters and environments appear as realistic live-action fantasy film assets. Scenes feature **natural skin texture**, **detailed fabrics**, **realistic creatures**, **practical materials**, **grounded lighting**, **atmospheric environments**, and **cinematic composition**. The result feels like a scene from a modern high-end fantasy film with believable characters and immersive environments.

  • LTX_2.3_Paper_Cut_Out_Style_LoRa↗

    vrgamedevgirl84

    This LoRA creates a cozy handcrafted **paper cut-out cinematic diorama** style where every subject and environment looks physically assembled from layered paper pieces. Scenes feature **stacked paper shapes**, **visible cut edges**, **layered sheets**, **folded paper elements**, **slight paper curl**, **tape seams**, and **handcrafted paper detailing**. The result feels like a miniature handmade storybook world built from paper. Objects, characters, and landscapes appear constructed from stacked paper layers with **clean cut edges**, **layered depth**, and **tactile dimension**. Lighting naturally highlights layered paper edges and overlapping shapes, giving a warm cinematic look while preserving the handcrafted paper aesthetic.

  • Huihui-Qwen3.8-27B-abliterated-GGUF↗

    k1lliiviie

    This is an uncensored version of Qwen/Qwen3.8-27B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. The newly added **Huihui-Qwen3.8-27B-abliterated-Underdog-Saluki** series come from ConwayResearch/Underdog-Saluki-27B-1.0 and ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF. Only layers **22 to 52 (0-based indexing)** have been ablated, while the other layers remain unablated. It may come with a small disclaimer warning. Due to ConwayResearch/Underdog-Saluki-27B-1.0 not providing an imatrix file, we will attempt to perform ablation by mixing the GGUF weights of Swift-1.5 and ConwayResearch/Underdog-Saluki-27B-1.0.

  • Huihui-Qwen3-Coder-30B-A3B-Instruct-abliterated↗

    huihui-ai

    This is an uncensored version of Qwen/Qwen3-Coder-30B-A3B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. Ablation was performed using a new and faster method, which yields better results. You can use huihui_ai/qwen3-coder-abliterated directly,