Goetia-26B-A4B-v1.3-Heretic-ARA-FP8-Dynamic is a Hugging Face model repository identified as a 26-billion-parameter, FP8 Dynamic model, but the available page content does not provide enough documentation to assess its behavior or suitability confidently. The model name includes “Heretic” and “ARA,” yet the source does not explicitly classify the model as uncensored, unrestricted, or abliterated, so those properties should not be assumed. Capabilities, supported modalities, context length, inference speed, pricing, training details, and recommended hardware are not disclosed in the available source. Consequently, no specific use case can be verified beyond general experimentation with a hosted model artifact; coding, agentic workflows, tool calling, vision, and reasoning performance remain undocumented. Developers should review the repository files and model card directly before deployment, especially for prompt format, quantization compatibility, runtime requirements, safety behavior, and evaluation results. Licensing terms are not disclosed in the supplied page content, so redistribution and commercial-use permissions require separate verification. The source is the Hugging Face repository, but no publication or update date is shown, making freshness beyond the current indexed page unavailable.

Model size: 26B parameters
Context: Not listed

Hugging Face

GRM-3.2-Sky-OPAL-GGUF

GRM-3.2-Sky-OPAL-GGUF is a Hugging Face-hosted, text-oriented model repository intended for reasoning workloads. The available record identifies text as its modality and reasoning as its use case, but it does not document specific capabilities such as coding, tool calling, vision, audio, or structured output. The supplied page content is primarily Hugging Face interface markup and does not expose a model card, parameter count, context-window specification, inference benchmark, pricing, or deployment guidance. Consequently, developers cannot verify the model’s scale, memory requirements, expected throughput, quality, or hardware suitability from this source alone. The repository name indicates a GGUF artifact, but supported quantization variants and runtime compatibility are not disclosed in the available content. Licensing terms are also not visible, so usage and redistribution requirements should be checked directly on the repository before adoption. The page snapshot contains no publication or update date, meaning source freshness cannot be independently established. Treat this entry as an unverified starting point and inspect the repository files and documentation before production use.

reasoning

Model size: Size not listed
Context: Not listed

Hugging Face

welmia-2.0-103m-instruct

welmia-2.0-103m-instruct is a small text-generation model intended for instruction-following tasks, but the available source provides very little technical documentation for evaluating it. It supports text as its listed modality, and the supplied record reports 103,000,000 parameters. No specific capabilities, benchmarks, context-window size, throughput results, pricing, or recommended workflows are disclosed. Accordingly, potential uses such as general text generation or lightweight instruction-based experimentation cannot be validated beyond the model’s text-generation classification; no supported use-case categories are identified. The source page does not expose a model card description, usage examples, evaluation results, safety guidance, or deployment requirements in the available content. Licensing terms and commercial-use permissions are also not disclosed, so those should be confirmed on Hugging Face before deployment. The page is hosted on Hugging Face at the model’s official repository URL, but it does not provide a publication or update date, meaning source freshness cannot be independently verified. Developers should treat this as an under-documented model and perform task-specific quality, reliability, and resource testing before adoption.

Model size: 103M parameters
Context: Not listed

Hugging Face

DeepSeek-V4-Flash-0731-EXL3-3.0bpw

DeepSeek-V4-Flash-0731-EXL3-3.0bpw is a Hugging Face model repository that may be relevant for coding workflows, but the available source page does not provide enough technical detail for a confident deployment decision. The model name identifies an EXL3 3.0bpw variant, indicating a quantized distribution, but the source does not disclose the underlying parameter count, context window, architecture details, hardware requirements, or inference performance. No tokens-per-second benchmark is reported for this exact model. The indexed record lists coding as a use case; other capabilities are not documented. Modalities are not specified, so text, vision, audio, and other input or output support should not be assumed. Pricing is not disclosed, and the provided page content does not state a license, usage restrictions, safety characteristics, or maintainer documentation. The repository is hosted at Hugging Face under the 0xSero namespace. The page metadata identifies the repository but provides no publication or update date, so source freshness cannot be independently verified from the available content. Review the repository files and license before using it in production, and validate compatibility with the intended EXL3 inference runtime.

coding

Model size: Size not listed
Context: Not listed

Hugging Face

Qwen3.8-27B-Claude-Opus-Reasoning-Distilled

Qwen3.8-27B-Claude-Opus-Reasoning-Distilled is a Hugging Face model intended for text-generation and reasoning workflows. The available record lists 27 billion parameters and text as its modality, making it potentially relevant for developers evaluating language-only reasoning tasks. However, the supplied Hugging Face page exposes no model-card documentation describing specific reasoning techniques, coding ability, tool use, agent behavior, supported languages, evaluation results, or inference requirements. Context-window size, throughput, pricing, and performance benchmarks are not disclosed, so suitability for latency-sensitive or long-context applications cannot be assessed from the available information. The source also does not disclose a license, safety policy, training data details, quantization formats, deployment instructions, or hardware guidance; these should be verified on the repository before adoption or redistribution. The page is hosted under the AnosVoldigoad11 Hugging Face account, and the supplied content confirms the repository and model title, but it provides no publication or update date. Consequently, source freshness cannot be established beyond the fact that the repository page was available for indexing. Treat this entry as a preliminary directory record and validate capabilities, licensing, and operational behavior directly before production use.

reasoning

Model size: 27B parameters
Context: Not listed

Hugging Face

multilingual-e5-small-GGUF

multilingual-e5-small-GGUF is a Hugging Face repository entry hosted by cstr, but the supplied page content does not disclose enough technical information to evaluate it for production use. The name identifies the GGUF format and the multilingual-E5-small designation; however, the source does not provide a parameter count, context window, inference benchmark, supported modalities, capability list, or deployment requirements. Its practical use cases are therefore not confirmed by the available material, and no use-case classification is assigned here. Developers should not assume embedding, retrieval, generation, multilingual, or other specific behavior without consulting a complete model card or testing the repository files directly. Licensing terms, safety guidance, quantization details, file variants, compatibility information, and model-specific limitations are also not disclosed in the supplied source. The official source is the Hugging Face page at https://huggingface.co/cstr/multilingual-e5-small-GGUF. The available HTML appears to be a general repository shell rather than a populated technical model card, and no publication or update date is shown, so source freshness cannot be established. Treat this entry as requiring verification before integration.

Model size: Size not listed
Context: Not listed

Hugging Face

rizzo-pii-0.3B-security

rizzo-pii-0.3B-security is a 300-million-parameter model listed for cybersecurity use, but the available source does not provide enough technical documentation to establish whether it is suitable for a particular production workload. The supplied Hugging Face page identifies the repository as dr3x1/rizzo-pii-0.3B-security, while its accessible metadata contains only Hugging Face’s generic site description and does not expose a model card, task description, benchmark results, inference speed, context window, or implementation guidance. Capabilities and supported modalities are not disclosed, so developers should not assume text generation, code analysis, classification, tool use, or other functionality without inspecting the repository files directly. Pricing is not disclosed and the model is hosted as an open repository on Hugging Face, but its license is not disclosed in the available source; verify licensing and usage restrictions before deployment. The model may be relevant for exploratory cybersecurity work, but its accuracy, safety characteristics, training data, and operational requirements cannot be evaluated from the supplied page. Source freshness is also not verifiable because no publication or update date is shown.

cybersecurity

Model size: 300M parameters
Context: Not listed

Hugging Face

moody-krea-mix

moody-krea-mix is not currently verifiable as an available, documented model from the supplied Hugging Face source. The page returns a 404 error, and its metadata identifies it only as a Hugging Face page rather than providing a model card, files, tags, task information, or usage instructions. No capabilities or modalities are disclosed, so developers should not assume support for text generation, image generation, vision, audio, coding, agents, or other workloads. Practical use cases therefore cannot be established from the available evidence. Parameter count, inference speed, pricing, context window, and performance benchmarks are not disclosed. Licensing terms, permitted uses, and any safety or content restrictions are also not disclosed; these should be confirmed from an accessible official repository or accompanying documentation before deployment. The supplied source snapshot is the freshest available evidence here, but it indicates that the referenced repository or page was unavailable at review time. Treat this record as an unverified reference rather than a usable production dependency, and avoid building integrations until the owner restores the page or provides a working artifact and license.

Model size: Size not listed
Context: Not listed

Hugging Face

Qwen3-Uncensored-TextEncoders-Klein-Z-Image-Anima-GGUF

Qwen3-Uncensored-TextEncoders-Klein-Z-Image-Anima-GGUF is a Hugging Face repository whose name identifies it as an uncensored GGUF package associated with text encoders and the Klein, Z-Image, and Anima names. The available source does not provide a model card, technical description, architecture details, parameter count, context window, inference benchmark, or setup instructions. Its practical role, supported modalities, and compatibility with particular applications are therefore not disclosed; the supplied record lists no modalities. The explicit uncensored classification may make it relevant for developers evaluating less-restricted text-encoding workflows, but the source does not document the underlying behavior, quality, safety properties, or performance, so those should be validated independently before deployment. No pricing information is provided, and licensing terms or usage restrictions are not disclosed in the supplied page content, making license review essential before redistribution or commercial use. The Hugging Face page is the stated source, but no publication or update date is visible in the supplied content, so source freshness cannot be established beyond the current indexed page snapshot.

uncensored

Model size: Size not listed
Context: Not listed

Hugging Face

Qwen3.8_4B_Distilled

Qwen3.8_4B_Distilled is a text-only model listed on Hugging Face with a recorded parameter count of 4 billion. The available source page identifies the repository as Ma7ee7/Qwen3.8_4B_Distilled, but it does not provide a model card description of capabilities, supported tasks, training details, evaluation results, context-window size, inference speed, or pricing. Accordingly, developers should treat its practical use cases as undisclosed rather than assume it is suitable for coding, reasoning, agents, generation, or other specialized workflows. The source also does not disclose a license, usage restrictions, safety classification, or deployment requirements, so licensing and operational suitability should be verified directly in the repository before adoption. No benchmark for tokens per second is reported. The page’s visible metadata is primarily generic Hugging Face site content, and no publication or update date for this specific model is provided; source freshness is therefore not established. This record may be useful as a pointer to the repository, but additional inspection of model files and documentation is necessary before selecting it for production or evaluating quality.

Model size: 4B parameters
Context: Not listed

Hugging Face

girlslike-krea2

girlslike-krea2 is a Hugging Face model repository intended for text-to-image generation, with text and image modalities listed in the available record. It may be relevant for developers exploring image-generation workflows, such as creating images from textual prompts, but the supplied source does not disclose supported interfaces, inference requirements, resolution limits, training data, or quality benchmarks. No parameter count or inference-speed benchmark is reported for this exact model, and pricing information is not provided. The repository page exposes standard Hugging Face metadata and a model thumbnail, but the supplied content does not include a substantive model card describing architecture, recommended prompts, hardware needs, or deployment steps. Licensing terms, usage restrictions, and safety guidance are also not disclosed in the available source, so these should be verified directly on the repository before commercial or public deployment. The source snapshot contains no publication or update date, meaning freshness cannot be independently confirmed. Treat this model as an undocumented or minimally documented text-to-image option until the repository provides more technical and licensing information.

Model size: Size not listed
Context: Not listed

Hugging Face

Funphantom

Funphantom is listed on Hugging Face, but the supplied page content does not disclose enough technical information to assess it for production use. The snapshot contains the repository title and URL, while omitting a model card, architecture description, parameter count, context window, supported modalities, capabilities, benchmarks, inference-speed measurements, pricing, and documented use cases. Accordingly, its suitability for coding, agents, reasoning, generation, or other workflows is not established. Developers should treat the model as unevaluated until the repository provides documentation describing inputs, outputs, runtime requirements, dependencies, and expected behavior. Licensing terms, acceptable-use conditions, safety guidance, and redistribution permissions are also not disclosed in the provided source and should be checked directly on Hugging Face before deployment or integration. The source freshness cannot be precisely determined because the supplied page contains no visible publication or update date; this assessment applies only to the provided page snapshot. Consult the official repository for any README, configuration files, model metadata, or later revisions before relying on Funphantom.

Model size: Size not listed
Context: Not listed

Hugging Face

Qwen3.8-9B-Distill-uncensored-heretic-GGUF

Qwen3.8-9B-Distill-uncensored-heretic-GGUF is a 9-billion-parameter GGUF model hosted on Hugging Face and listed for tool-calling, uncensored use, and reasoning. Its recorded capabilities include tool-calling and the uncensored classification, making it a candidate for local or self-managed assistants that need structured tool interaction or reasoning workflows. The provided record does not identify any supported input or output modalities, so multimodal functionality is not disclosed. Context-window size, inference speed, pricing, and task-specific benchmark results are also not disclosed; developers should validate these details with the repository files and their chosen GGUF runtime before deployment. The supplied page capture exposes the repository title and generic Hugging Face metadata but does not include substantive model-card documentation, configuration guidance, quantization recommendations, or evaluation results. Licensing terms are not disclosed in the available source content and should be checked directly on the repository before redistribution or commercial use. No source revision date is visible, so the freshness of the model documentation cannot be established from the supplied page.

tool-callinguncensoredreasoning

Model size: 9B parameters
Context: Not listed

Hugging Face

Qwen3.8-27B-oQ6e-mtp

Qwen3.8-27B-oQ6e-mtp is a Hugging Face model repository with insufficient public documentation in the supplied source to determine whether it is suitable for a specific application. The model name and record indicate 27 billion parameters, but the page content provided does not document supported capabilities, modalities, context length, inference speed, pricing, or practical performance. No use cases are explicitly identified, so developers should not assume coding, reasoning, tool-calling, vision, audio, or other specialized functionality. The repository page also does not provide enough information to assess deployment requirements, quantization behavior, compatibility, safety characteristics, or output reliability. Licensing terms are not disclosed in the supplied page content and should be verified directly on Hugging Face before redistribution or commercial use. The source is a Hugging Face repository page indexed as a model record; no publication, update, or benchmark date is visible in the supplied content, so source freshness cannot be established. This model should therefore be evaluated only after reviewing its complete model card, files, license, runtime requirements, and task-specific benchmarks.

Model size: 27B parameters
Context: Not listed

Hugging Face

silero-models-v5-cis-base-nostress

silero-models-v5-cis-base-nostress is a Hugging Face model intended for text-to-speech and is most relevant when an application needs to convert text into spoken audio. The available model record identifies text and audio as its modalities and lists audio as its use case. This makes it a candidate for speech generation in accessibility tools, voice interfaces, narration, and other audio-producing workflows, although the supplied source does not document supported languages, voice options, quality characteristics, runtime requirements, or integration instructions. The model page does not explicitly disclose a parameter count, inference-speed benchmark, context window, pricing, or detailed capabilities. Licensing terms and commercial-use permissions are also not disclosed in the available source content, so they should be verified directly on the Hugging Face repository before deployment. The supplied page snapshot confirms the repository title, canonical URL, and Hugging Face hosting, but exposes no substantive model-card details beyond the model’s text-to-speech purpose. Developers should therefore treat compatibility, output quality, language coverage, and operational performance as unverified until they inspect the repository files and test the model in their target environment.

audio

Model size: Size not listed
Context: Not listed

Hugging Face

endless-frontier-BigBang-v1-8-bit-MTPLX

endless-frontier-BigBang-v1-8-bit-MTPLX cannot currently be evaluated as a usable model because its Hugging Face source page returns a 404 error. The supplied source contains no model card, repository files, metadata, documentation, benchmark results, or usage instructions for this exact model. Its capabilities and modalities are not disclosed, so there is no supported basis for recommending it for coding, agents, reasoning, vision, generation, embeddings, or other workloads. Practical use cases are therefore undetermined rather than established. The model’s parameter count, inference speed, context window, pricing, and deployment requirements are also not disclosed. Licensing terms and any safety, content, or usage restrictions cannot be verified from the available source, so prospective users should avoid assuming that the name or apparent quantization reference establishes a license or performance profile. The source URL is the official Hugging Face URL recorded for this entry, but its current 404 response indicates that the repository may be unavailable, renamed, private, or removed. Verify the repository and obtain authoritative documentation before considering deployment.

Model size: Size not listed
Context: Not listed

Hugging Face

moziAI-35B-Qwen3.6-A3B-Ornith

moziAI-35B-Qwen3.6-A3B-Ornith is listed as a 35-billion-parameter text model with tool-calling and uncensored capabilities. The directory record associates it with tool-calling, uncensored use, vision-related tasks, and finance, but its declared modality is text only; therefore, vision support is not independently established by the supplied source. The available Hugging Face HTML does not match the requested repository: it identifies chenyumo/moziAI-35B-A3B-MOE-MTP rather than moziAI-35B-Qwen3.6-A3B-Ornith. This repository mismatch is an important verification limitation before deployment. The supplied material does not disclose a context window, inference-speed benchmark, pricing, licensing terms, safety documentation, or implementation details. No performance ranking or production-readiness claim can be made from the available evidence. The source is Hugging Face, but the freshness of information for this exact model cannot be established because the retrieved page points to a different model. Developers should verify the exact repository, model card, files, license, supported inference framework, and modality claims before using it in tool-enabled, finance, or other production workflows.

tool-callinguncensoredvisionfinance

Model size: 35B parameters
Context: Not listed

Hugging Face

Qwen3.8-27B-Whitehat-GGUF

Qwen3.8-27B-Whitehat-GGUF is a 27-billion-parameter image-text-to-text model listed on Hugging Face. The available record identifies image and text modalities, with tool-calling as a documented capability. It may therefore be relevant for applications that combine visual and textual inputs with tool-oriented workflows, including tool-calling, vision, and cybersecurity use cases. However, the supplied Hugging Face page content does not expose a detailed model card, prompting guidance, architecture description, evaluation results, or inference benchmarks. Context-window size, tokens-per-second performance, pricing, and deployment requirements are not disclosed. The source also does not disclose a license, so licensing compatibility should be verified directly on the Hugging Face repository before redistribution or commercial use. The model name indicates the 27B parameter scale, but no additional performance or safety conclusions should be inferred from that label. The repository is the primary available source, and the supplied page snapshot confirms its existence but provides no dated release or update information; source freshness therefore cannot be independently established from the available material. Developers should validate vision handling, tool-call formats, cybersecurity behavior, and runtime compatibility with the specific GGUF quantization they intend to deploy.

tool-callingvisioncybersecurity

Model size: 27B parameters
Context: Not listed

Hugging Face

OBLITERATUS-Qwen3.8-27B-OBLITERATED-unsloth-mlx

OBLITERATUS-Qwen3.8-27B-OBLITERATED-unsloth-mlx is a text-generation model intended for developers researching uncensored or abliterated language-model behavior. Its listed modalities are text, and its recorded capabilities are uncensored and abliterated operation. The model is identified as a 27-billion-parameter model, making it a potentially substantial local deployment workload, although the supplied source does not disclose hardware requirements, quantization details, context-window size, throughput, or quality benchmarks. Practical recorded use cases are uncensored experimentation, abliterated-model research, and general research workflows; no evidence is provided for vision, audio, tool calling, agents, coding specialization, or other modality-specific features. Pricing is not disclosed, and no license terms or usage restrictions are visible in the supplied source content, so licensing should be verified directly on the Hugging Face model page before redistribution or commercial use. The source is Hugging Face, and the page is currently indexed as a text-generation model. However, the supplied page capture does not disclose a publication or last-update date, so source freshness beyond the current indexing is not established.

uncensoredabliteratedresearch

Model size: 27B parameters
Context: Not listed

Hugging Face

Huihui-Qwen3.8-27B-Abliterated-INT4-W4A16-AutoRound

Huihui-Qwen3.8-27B-Abliterated-INT4-W4A16-AutoRound is a 27-billion-parameter, INT4 W4A16 AutoRound model intended for image-text-to-text use. Its recorded modalities are image and text, and “abliterated” is explicitly part of the model name and listed capability. A practical fit is experimentation with multimodal prompts that combine images and text, particularly when evaluating an abliterated model variant. The available source material does not disclose a context window, inference speed, pricing, detailed benchmark results, training information, or implementation guidance, so deployment suitability and resource requirements cannot be assessed from this record alone. The model card content provided is limited to Hugging Face page metadata and does not expose a license, so licensing and redistribution terms should be verified directly on the source page before commercial or hosted use. Safety behavior, reliability, and output quality are also not documented here; the “abliterated” label should not be treated as a performance or safety guarantee. The source is the model’s Hugging Face repository, but its publication or last-update date is not disclosed, so source freshness cannot be independently established.

abliteratedvision

Model size: 27B parameters
Context: Not listed

Hugging Face

translate-gemma-4-sub-e2b-GGUF

translate-gemma-4-sub-e2b-GGUF is a Hugging Face-hosted model repository presented in GGUF format, but the available source snapshot provides very little technical documentation. The directory record identifies image and text as its modalities and lists vision as a use case, so it may be relevant for applications that process visual and textual inputs. The model name suggests a translation-oriented Gemma variant, but the source does not provide a model card or sufficient details to verify supported language pairs, translation quality, architecture, quantization settings, runtime requirements, context length, or recommended hardware. Parameter count, inference speed, pricing, and benchmark results are not disclosed. Developers should therefore treat this repository as an experimental or insufficiently documented option until they inspect its files and test it in their target GGUF-compatible runtime. Licensing terms, usage restrictions, safety guidance, and commercial-use conditions are also not disclosed in the supplied source, so these should be verified directly on Hugging Face before deployment. The source is the current Hugging Face repository page supplied for this entry, but it contains no visible publication or update date, making repository freshness beyond the captured page unavailable.

vision

Model size: Size not listed
Context: Not listed