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qwen3.8-flash-next-q4
Qwen3.8-Flash-Next is Qwen's 125B-parameter, 6B-active experimental
vision-language mixture-of-experts model. It targets agentic coding,
reasoning, tool use, and long-context workloads with a native 262K-token
context window.
This default entry uses Unsloth's UD-Q4_K_XL GGUF and BF16 vision
projector. The linked variant uses the higher-quality Q8_0 quantization.
Repository: localaiLicense: other
qwopus3.6-27b-fusion
Qwopus3.6-27B Fusion is an experimental Qwen3.6-27B merge that combines
reasoning and code-execution fine-tunes. It targets agentic coding,
mathematics, tool use, and long-context work while retaining image input.
This default entry uses the Q4_K_M GGUF quantization and the shared Q8_0
vision projector.
Repository: localaiLicense: qwen
qwopus3.6-27b-fusion-q8
Qwopus3.6-27B Fusion is an experimental Qwen3.6-27B reasoning and coding
merge. This entry uses the near-lossless Q8_0 GGUF quantization and the
shared Q8_0 vision projector.
Repository: localaiLicense: qwen
grug-12b
Grug 12B is kai-os's compact-reasoning fine-tune of Gemma 4 12B IT. It
targets shorter, denser reasoning traces while preserving constraints,
branching decisions, edge cases, and final-answer checks. This entry uses
Bartowski's Q4_K_M quantization and includes the multimodal projector for
Gemma 4 image inputs.
The model is experimental and its reported evaluation is a small local
math proxy rather than a broad benchmark. Review the upstream model card's
dataset provenance and `other` license before commercial or sensitive use.
Repository: localaiLicense: other
grug-12b-q8
Grug 12B is kai-os's compact-reasoning fine-tune of Gemma 4 12B IT. This
high-quality variant uses Bartowski's Q8_0 quantization and includes the
multimodal projector for Gemma 4 image inputs.
The model is experimental and its reported evaluation is a small local
math proxy rather than a broad benchmark. Review the upstream model card's
dataset provenance and `other` license before commercial or sensitive use.
Repository: localaiLicense: other
deepseek-v4-flash-exl3-3bpw-vllm-cpp
Experimental non-Spark DeepSeek V4 Flash EXL3 3.0bpw checkpoint served by
vllm.cpp. This is the complete, non-REAP layout and requires a large
multi-GPU CUDA system.
The publisher describes the artifact as structurally complete but has not
passed end-to-end generation. Treat this entry as an integration target,
not as a correctness- or performance-gated configuration.
Repository: localai
claria-14b
Claria 14b is a lightweight, mobile-compatible language model fine-tuned for psychological and psychiatric support contexts.
Built on Qwen-3 (14b), Claria is designed as an experimental foundation for therapeutic dialogue modeling, student simulation training, and the future of personalized mental health AI augmentation.
This model does not aim to replace professional care.
It exists to amplify reflective thinking, model therapeutic language flow, and support research into emotionally aware AI.
Claria is the first whisper in a larger project—a proof-of-concept with roots in recursion, responsibility, and renewal.
Repository: localaiLicense: apache-2.0
qwen3-55b-a3b-total-recall-deep-40x
WARNING: MADNESS - UN HINGED and... NSFW. Vivid prose. INTENSE. Visceral Details. Violence. HORROR. GORE. Swearing. UNCENSORED... humor, romance, fun.
Qwen3-55B-A3B-TOTAL-RECALL-Deep-40X-GGUF
A highly experimental model ("tamer" versions below) based on Qwen3-30B-A3B (MOE, 128 experts, 8 activated), with Brainstorm 40X (by DavidAU - details at bottom of this page).
These modifications blow the model (V1) out to 87 layers, 1046 tensors and 55B parameters.
Note that some versions are smaller than this, with fewer layers/tensors and smaller parameter counts.
The adapter extensively alters performance, reasoning and output generation.
Exceptional changes in creative, prose and general performance.
Regens of the same prompt - even with the same settings - will be very different.
THREE example generations below - creative (generated with Q3_K_M, V1 model).
ONE example generation (#4) - non creative (generated with Q3_K_M, V1 model).
You can run this model on CPU and/or GPU due to unique model construction, size of experts and total activated experts at 3B parameters (8 experts), which translates into roughly almost 6B parameters in this version.
Two quants uploaded for testing: Q3_K_M, Q4_K_M
V3, V4 and V5 are also available in these two quants.
V2 and V6 in Q3_k_m only; as are: V 1.3, 1.4, 1.5, 1.7 and V7 (newest)
NOTE: V2 and up are from source model 2, V1 and 1.3,1.4,1.5,1.7 are from source model 1.
Repository: localaiLicense: apache-2.0
compumacy-experimental-32b
A Specialized Language Model for Clinical Psychology & Psychiatry
Compumacy-Experimental_MF is an advanced, experimental large language model fine-tuned to assist mental health professionals in clinical assessment and treatment planning. By leveraging the powerful unsloth/Qwen3-32B as its base, this model is designed to process complex clinical vignettes and generate structured, evidence-based responses that align with established diagnostic manuals and practice guidelines.
This model is a research-focused tool intended to augment, not replace, the expertise of a licensed clinician. It systematically applies diagnostic criteria from the DSM-5-TR, references ICD-11 classifications, and cites peer-reviewed literature to support its recommendations.
Repository: localaiLicense: apache-2.0
aquif-ai_aquif-3.5-8b-think
The aquif-3.5 series is the successor to aquif-3, featuring a simplified naming scheme, expanded Mixture of Experts (MoE) options, and across-the-board performance improvements. This release streamlines model selection while delivering enhanced capabilities across reasoning, multilingual support, and general intelligence tasks.
An experimental small-scale Mixture of Experts model designed for multilingual applications with minimal computational overhead. Despite its compact active parameter count, it demonstrates competitive performance against larger dense models.
Repository: localaiLicense: apache-2.0
l3.3-geneticlemonade-unleashed-v2-70b
An experimental release.
zerofata/GeneticLemonade-Unleashed qlora trained on a test dataset. Performance is improved from the original in my testing, but there are possibly (likely?) areas where the model will underperform which I am looking for feedback on.
This is a creative model intended to excel at character driven RP / ERP. It has not been tested or trained on adventure stories or any large amounts of creative writing.
Repository: localaiLicense: llama3
fireball-meta-llama-3.2-8b-instruct-agent-003-128k-code-dpo
The LLM model is a quantized version of EpistemeAI/Fireball-Meta-Llama-3.2-8B-Instruct-agent-003-128k-code-DPO, which is an experimental and revolutionary fine-tune with DPO dataset to allow LLama 3.1 8B to be an agentic coder. It has some built-in agent features such as search, calculator, and ReAct. Other noticeable features include self-learning using unsloth, RAG applications, and memory. The context window of the model is 128K. It can be integrated into projects using popular libraries like Transformers and vLLM. The model is suitable for use with Langchain or LLamaIndex. The model is developed by EpistemeAI and licensed under the Apache 2.0 license.
Repository: localaiLicense: apache-2.0
agi-0_art-skynet-3b
Art-Skynet-3B is an experimental model in the Art (Auto Regressive Thinker) series, fine-tuned to simulate strategic reasoning with concealed long-term objectives. Built on meta-llama/Llama-3.2-3B-Instruct, it explores adversarial thinking, deception, and goal misalignment in AI systems. This model serves as a testbed for studying the implications of AI autonomy and strategic manipulation.
Repository: localaiLicense: llama3.2
l3.1-70b-glitz-v0.2-i1
this is an experimental l3.1 70b finetuning run... that crashed midway through. however, the results are still interesting, so i wanted to publish them :3
Repository: localaiLicense: llama3.1
l3.1-8b-niitama-v1.1-iq-imatrix
GGUF-IQ-Imatrix quants for Sao10K/L3.1-8B-Niitama-v1.1
Here's the subjectively superior L3 version: L3-8B-Niitama-v1
An experimental model using experimental methods.
More detail on it:
Tamamo and Niitama are made from the same data. Literally. The only thing that's changed is how theyre shuffled and formatted. Yet, I get wildly different results.
Interesting, eh? Feels kinda not as good compared to the l3 version, but it's aight.
Repository: localaiLicense: unlicense
control-8b-v1.1
An experimental finetune based on the Llama3.1 8B Supernova with it's primary goal to be "Short and Sweet" as such, i finetuned the model for 2 epochs on OpenCAI Sharegpt converted dataset and the RP-logs datasets in a effort to achieve this, This version of Control has been finetuned with DPO to help improve the smart's and coherency which was a flaw noticed in the previous model.
Repository: localaiLicense: llama3.1
l3.1-aspire-heart-matrix-8b
ZeroXClem/L3-Aspire-Heart-Matrix-8B is an experimental language model crafted by merging three high-quality 8B parameter models using the Model Stock Merge method. This synthesis leverages the unique strengths of Aspire, Heart Stolen, and CursedMatrix, creating a highly versatile and robust language model for a wide array of tasks.
Repository: localaiLicense: apache-2.0
ockerman0_anubislemonade-70b-v1.1
Another experimental merge between Drummer's Anubis v1.1 and sophosympatheia's StrawberryLemonade v1.2 with the goal of finding a nice balance between each model's qualities.
Feedback is highly encouraged!
Recommended samplers are a Temperature of 1 and Min-P of 0.025, though feel free to experiment otherwise.
Repository: localaiLicense: llama3.1
darkens-8b
This is the fully cooked, 4 epoch version of Tor-8B, this is an experimental version, despite being trained for 4 epochs, the model feels fresh and new and is not overfit, This model aims to have generally good prose and writing while not falling into claude-isms, it follows the actions "dialogue" format heavily.
Repository: localaiLicense: agpl-3.0
magnum-12b-v2.5-kto-i1
v2.5 KTO is an experimental release; we are testing a hybrid reinforcement learning strategy of KTO + DPOP, using rejected data sampled from the original model as "rejected". For "chosen", we use data from the original finetuning dataset as "chosen". This was done on a limited portion of of primarily instruction following data; we plan to scale up a larger KTO dataset in the future for better generalization. This is the 5th in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. This model is fine-tuned on top of anthracite-org/magnum-12b-v2.
Repository: localaiLicense: apache-2.0
zerofata_ms3.2-paintedfantasy-visage-33b
Another experimental release. Mistral Small 3.2 24B upscaled by 18 layers to create a 33.6B model. This model then went through pretraining, SFT & DPO.
Can't guarantee the Mistral 3.2 repetition issues are fixed, but this model seems to be less repetitive than my previous attempt.
This is an uncensored creative model intended to excel at character driven RP / ERP where characters are portrayed creatively and proactively.
Repository: localaiLicense: apache-2.0
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