DeepSeek R1 Distill Qwen 14B Alternatives

DeepSeek-R1-0528-Qwen3-8B is a large open-source language model designed for advanced text generation and understanding. It is suitable for developers and researchers seeking a robust model for NLP applications, with support for local deployment and Docker integration.

This repository provides an RKLLM quantized build (w8a8_g128) of the DeepSeek-R1-Distill-Qwen-14B model specifically compiled for RK3588-based single-board computers. It enables local LLM inference on edge devices with a simple Flask server deployment option. The model targets embedded AI applications where cloud connectivity is limited.

DeepSeek-R1-0528 is an open-weight reasoning model released by DeepSeek. It excels at step-by-step reasoning and complex problem solving. The model is available for local download and cloud inference on Hugging Face.

This is a distilled 8B parameter model from the DeepSeek-R1 series, based on the Llama architecture. It retains strong reasoning and problem-solving abilities from the larger teacher model while being significantly more efficient. The model is suitable for local inference, coding assistance, and complex reasoning tasks.

DeepSeek-V3.1 is the latest iteration of DeepSeek's open foundation model series. It features a sophisticated chat template, support for tool calling, and strong performance on reasoning tasks. The model is fully open and can be run locally or deployed via standard inference frameworks.

A GGUF-quantized version of a distilled 70B Llama model based on DeepSeek-R1. Optimized for local inference with support for tool calling and reasoning. It is designed for efficient execution using llama.cpp or similar runtimes on CPUs or GPUs.

This GGUF-quantized model is a community conversion of DeepSeek-R1-0528 based on the Qwen3 8B architecture. It is optimized for local inference using tools such as LM Studio or llama.cpp. The model supports advanced features including structured tool calling and chain-of-thought reasoning while running efficiently on modest hardware.

This model is an 8-bit quantized version of DeepSeek-R1-0528 based on the Qwen3 8B architecture, optimized for the MLX framework used on Apple Silicon. It includes a custom chat template and is distributed by the lmstudio-community on Hugging Face for local inference.

DeepSeek-R1 is an open-source large language model developed by DeepSeek AI for text generation and conversational AI. It is suitable for developers and researchers building chatbots, virtual assistants, and other NLP applications.

QuantTrio/DeepSeek-V3.2-AWQ is a quantized (AWQ) version of DeepSeek's V3.2 large language model. It includes a custom chat template and tokenizer optimized for efficient inference. The model is suitable for local deployment where full-precision weights would be too large.

DeepSeek R1 is an open-source artificial intelligence model designed for advanced reasoning, mathematics, coding, and natural language understanding. Built on a Mixture of Experts (MoE) architecture, it features 37 billion activated parameters and a total of 671 billion parameters, supporting up to a 128,000 token context length. The model leverages advanced reinforcement learning techniques to achieve self-verification, multi-step reflection, and human-aligned reasoning. 3% of Codeforces participants, positioning it among the top-performing AI models globally. The platform is accessible online for free without requiring login and offers in-browser inference using WebGPU acceleration. js and ONNX Runtime Web, ensuring that no data is sent to a server and enabling offline use once loaded. 5 billion to 70 billion parameters. These distilled versions are optimized for commercial use and can be downloaded, with some based on Qwen and Llama architectures. The model is particularly suited for complex problem-solving, multilingual understanding, and production-grade code generation. A notable feature is its chain-of-thought visualization capability, which addresses AI interpretability challenges. 19 per million output tokens. The intelligent caching system offers significant cost savings for repeated queries. The model weights are released under the MIT license, supporting open-source and commercial applications. Ongoing development includes plans for multimodal support, conversational enhancements, and distributed inference optimization, with contributions driven by the open-source community. As a state-of-the-art reasoning model, DeepSeek R1 offers a combination of high performance, affordability, and accessibility for developers, researchers, and organizations seeking advanced AI capabilities in reasoning, mathematics, and code generation.

DeepSeek-V2-Lite is a smaller, more efficient variant of the DeepSeek-V2 large language model. It uses a mixture-of-experts architecture to deliver strong performance while requiring fewer resources for inference. The model supports chat interactions and is available on Hugging Face for developers to integrate into applications.

DeepSeek-V4-Pro is an open-source large language model released by deepseek-ai. It supports text generation, fine-tuning, and inference via API or CLI, making it suitable for AI research, development, and custom NLP applications.

This is a quantized and distilled version of the DeepSeek-R1 reasoning model based on Llama architecture. It is hosted on Hugging Face for download and local inference using libraries such as transformers or llama.cpp. The model supports advanced features including tool calling and is optimized for on-device or local deployment with significantly reduced memory footprint while retaining strong reasoning capabilities.

An FP4 quantized and optimized version of the DeepSeek-R1 model provided by NVIDIA. It is designed for efficient inference on NVIDIA GPUs while maintaining reasoning capabilities. The model uses a custom chat template and is suitable for developers building AI applications that require strong reasoning performance with lower memory footprint.