# Low-resource Deployment

DeepSeek-R1-Distill-Qwen-14B is an optimized large language model with a parameter scale of 14B, released by DeepSeek AI. It is distilled from the Qwen architecture and offers multiple GGUF quantization versions to improve performance.

AceReason-Nemotron-7B is a large language model based on the Nemotron architecture with 7B parameters, offering multiple quantized versions to accommodate different hardware requirements.

A Llamacpp imatrix quantized version based on allura-org/Q3-30B-A3B-Designant, suitable for various quantization needs, supporting role-playing and conversational tasks.

AM-Thinking-v1 is a text generation model based on the GGUF format, suitable for various natural language processing tasks.

Quantized version of INTELLECT-2, optimized using llama.cpp, supporting multiple quantization types to accommodate different hardware requirements.

Llamacpp quantized version based on andrewzh's Absolute_Zero_Reasoner-Coder-7b model, supporting multiple quantization levels, suitable for reasoning and code generation tasks.

This is the Llamacpp imatrix quantized version of the NVIDIA OpenCodeReasoning-Nemotron-14B model, suitable for code reasoning tasks.

NVIDIA Parakeet TDT 0.6B V2 is a model based on automatic speech recognition (ASR) tasks, suitable for English speech-to-text tasks.

This is a quantized version of the Qwen3-8B model, using llama.cpp for iMatrix quantization, suitable for chat scenarios.

Medra is a medical domain-specific QA and summarization model supporting English and Romanian, designed for medical AI applications.

Remnant-GLM4-32B is a 32B-parameter large language model based on the GLM4 architecture, supporting role-playing and conversational interactions, particularly suitable for salamander-related applications.

This is the quantized version of the Qwen3-8B-abliterated model, quantized using llama.cpp, suitable for text generation tasks.

Deepthink-1.5B-Open-PRM is a 1.5B parameter open-source language model, converted to GGUF format for use with llama.cpp.

This is the quantized version of the pixtral-12b model, quantized using llama.cpp, supporting image-text-to-text tasks.

A quantized version based on Gemma 2.9B, optimized using llama.cpp, suitable for running in LM Studio.

Qwen2.5 is the latest series of the Qwen large language model, featuring a 1.5B parameter instruction-tuned model that supports multilingual and long text generation.

This is a text-to-speech model based on the MLX format, supporting multiple languages and suitable for speech synthesis tasks.

DeepCoder-1.5B-Preview is a large language model for code reasoning, fine-tuned from DeepSeek-R1-Distilled-Qwen-1.5B through distributed reinforcement learning, capable of handling longer context lengths.

This is a GGUF format model converted from the slim-orpheus-3b-JAPANESE-ft model, specifically optimized for Japanese text processing.

Phi-4 Reasoning is a cutting-edge open-weight reasoning model based on Phi-4, fine-tuned with supervised chain-of-thought trajectory datasets and trained via reinforcement learning, specializing in mathematics, science, and programming skills.

MiniMaid-L2 is a role-play specialized model further optimized from MiniMaid-L1, achieving outstanding performance among 3B-scale models through knowledge distillation and training on a larger dataset.

Quantized version of OpenThinker2-7B, using llama.cpp for quantization, suitable for text generation tasks.

This model is a GGUF format conversion of canopylabs/orpheus-3b-0.1-ft, suitable for text generation tasks.

This model is a GGUF-format conversion of canopylabs/orpheus-3b-0.1-ft, suitable for text generation tasks.

Text generation model fine-tuned based on google/gemma-2b-it, supporting tool call reasoning process

Gemma 3 is a lightweight multimodal open model from Google that supports text and image inputs with text outputs, featuring a 128K large context window and support for 140+ languages.

This is the static quantized version of the asif00/orpheus-bangla-tts model, supporting Bengali text-to-speech tasks.

This is a GGUF format model converted from canopylabs/orpheus-3b-0.1-ft, suitable for text-to-speech tasks.

This is a GGUF format model converted from the canopylabs/orpheus-3b-0.1-ft model, suitable for text generation tasks.

This is a statically quantized version of the knowledgator/Qwen-encoder-0.5B model, primarily designed for text encoding tasks.

An 8B-parameter open-source large language model released by NVIDIA, based on the Llama-3 architecture, offering multiple quantization versions

A statically quantized model based on webbigdata/gemma-2-2b-jpn-it-translate, supporting translation tasks between Japanese and English.

A large language model based on 12B parameters, supporting text generation tasks, released under the Apache-2.0 license.

This is a text ranking model used for reordering and scoring texts to improve the relevance of search results.

Gemma 3 12B is a large language model that provides a quantized version in GGUF format, suitable for local deployment and use.

A 50-million-parameter text reranking model based on the Qwen2.5 architecture, suitable for information retrieval and document ranking tasks

Gemma 3 is a lightweight open model series launched by Google, built on the same technology as Gemini, supporting multimodal input and text output.

OlympicCoder-7B is a 7B-parameter large language model focused on code generation, based on open-r1/OlympicCoder-7B with llama.cpp quantization, supporting multiple quantization level options.

FinanceConnect-13B is a 13B-parameter large language model specialized in the financial domain, supporting natural language processing tasks such as summarization, classification, and translation.

This is the quantized version of openai/whisper-large-v3, employing INT4 weight quantization and FP16 activation quantization, suitable for vLLM inference.