LLM AI model

@extreamcode

Hi, I can see you’re not just asking for a local model , you’re aiming for a private system that behaves like ChatGPT Astra without depending on cloud APIs. That usually means the real challenge is making the model useful, responsive, and stable on your hardware, not just running it once. I’ve built practical AI and web integrations with Python, Flask/FastAPI, API workflows, and automation, so I can help you choose the right local stack, wire up the interface, and shape the prompting/routing layer for complex tasks. I’ve shared an initial estimate based on your description, and once we go over a few technical or functional details, I’ll confirm the exact cost and delivery schedule. If you already have a preferred model family, GPU setup, or target use case, I can align the implementation around that and keep everything clear and manageable. What hardware and interface style do you want for the local LLM setup? Best regards, Asad Could you share which hardware you plan to run this on, and whether you want a desktop app, web app, or API service? Do you need voice, file handling, or tool use in the first version? Looking forward to your reply so we can finalize the exact plan.

@sabaehsan

Greetings, It seems you’re looking for a local LLM AI model that can tackle complex tasks in a manner similar to ChatGPT Astra. My approach would involve developing a tailored AI model that understands and responds accurately to user inputs, drawing from my experience in AI development and training data management. I have a solid background in programming, including R, which will help in fine-tuning the model to meet your specific needs. With skills in translation and statistics, I can ensure that the model not only communicates effectively but also understands context in different languages, including German. My experience with AI chatbot development will further ensure that the end product is user-friendly and efficient. I’m excited about the possibility of working on this project and bringing your vision to life. Best regards, Saba Ehsan

@ZohaibSathio

Hi, a language model that runs on your own hardware, no API calls leaving the machine. The limit is VRAM, not cleverness. A quantised 7B or 14B does most of it, but multi step work needs a loop around the model rather than a bigger model. How I would build it: Ollama as the runtime, a model quantised to fit your card, then an agent loop over it that plans, calls tools and checks its own output before replying. Your files sit in a local vector store. What GPU is this running on? Closest I have shipped is an agentic assistant for a bank that plans, calls internal tools then answers, same loop shape as this. Happy to take the first milestone. Regards, Zohaib

@Digitalizers010

Hi, a model that runs on your own hardware and still handles long multi step requests, not one shot answers. Running it locally is the easy half. Holding quality once it's quantised to fit your card is the real work. How we'd build it: an open weight model behind an OpenAI compatible endpoint, quantised to your GPU, a tool calling layer so it can read files or run code instead of guessing, then a retrieval store over your own documents. What hardware is this meant to run on? We built a retrieval chatbot for a diagnostics lab that couldn't let its data leave the building. Happy to take a first milestone so you can judge the output early. Regards, Digitalizers

@longngoc2307

==== Hi - Truong here ==== "LOCAL LLM AI MODEL" - you need a local model that can handle multi-step ChatGPT-style tasks without sending your data to a hosted API. I’d start by choosing the model around your hardware and required German/English performance, then add a simple local chat layer with prompt templates and tool support. The main edge case is memory and context size, which can quickly make a local model slow or unstable. What GPU/RAM setup will the model need to run on? Looking forward to work with you.

@imraz2016

Hi, I can help select and deploy a powerful local LLM setup for complex ChatGPT-style tasks, with the model running on your own hardware/server. I can evaluate the best open-weight model for your available GPU/RAM, configure inference, tool/function calling, RAG, document processing and a ChatGPT-style interface, then optimize performance and memory usage. I can start immediately.

@SoftSandila

An LLM model task - before I quote, three things: 1. What should the model do - chat, classification, extraction, or coding? 2. Fine-tune an open model, or wire an existing API (Gemini/Claude/OpenAI)? 3. What data do you have to train/test with? Scope: the model + a small test harness that proves it on your data. I do LLM/AI work daily (4.9/5, 153 reviews). Answer the 3 and I send the plan before you commit.

@sara0346

Hello, I reviewed your project and understand you need a local LLM capable of handling complex tasks similar to ChatGPT Astra while operating independently from cloud AI services. I am ready to start immediately and will focus on a practical local architecture that balances model capability, speed and resource usage. I will evaluate suitable open-source LLMs, configure local inference and build the required interaction layer for complex reasoning, translation, statistics and chatbot tasks. The setup will be designed for offline use where possible, with clear installation and configuration instructions so the model can be extended later. Best Regards, Sara

@UzairPatell

We have the expertise needed to develop a local LLM AI model tailored to your specifications and ready to tackle complex tasks similar to ChatGPT Astra. Understanding your requirement for a model that excels in nuanced interactions, we can ensure it meets the performance standards you expect. Our familiarity with AI frameworks and local deployment strategies uniquely positions us to deliver effectively. We noticed the emphasis on handling complex tasks and would love to clarify whether there are specific use cases or datasets you have in mind to guide the model's training. With our experience in AI development and a commitment to quality, we're confident in our ability to meet your needs efficiently. We're happy to discuss the specifics further and ensure you leave with valuable insights, regardless of the outcome. Regards, Uzair.

@olaposif

Local LLM specialist with 11+ years deploying open-source AI models. Expert in Llama/Mistral/Qwen fine-tuning for complex tasks (reasoning, coding, analysis), local deployment (Ollama/vLLM/LM Studio), German translation, statistics, R integration, and ChatGPT-style interfaces. I'll recommend/set up the best local model for your needs. Ready to discuss your hardware and requirements. Let's build your local AI!

@manishashree12

Hello there, I specialize in developing AI models, including LLM models similar to ChatGPT Astra. I can create a custom LLM AI model tailored to handle complex tasks efficiently. Let's discuss how I can assist you further. Thanks, Manisha

@hakan1022

Hi, there I recently delivered a self‑hosted LLM solution for a fintech client, deploying a 13B model on a single 48 GB GPU server, achieving <200 ms inference latency for multi‑turn dialogues. I am planning to fine‑tune an open‑source foundation model with your domain data, integrate a prompt‑generation pipeline that auto‑expands user queries into structured prompts, and expose a GraphQL API for real‑time conversational UI. For the architecture, I will containerize the inference server with NVIDIA Triton, use a custom tokeniser cache to reduce load, and set up a hybrid caching layer that stores the most frequent responses in Redis. Similar projects required implementing a dynamic prompt rewriting module that reduced hallucinations by 35 % and increased response relevance. If I use my previous experience, your project will likely be completed successfully. Hope to discuss this in detail. Through detailed discussion, I think I can find the better solution to finish your project successfully. Thank you

@TarimShayan

Hi, Let's cut right to the chase - no fluff, no wasted time. You need LLM AI model done right, and you need it done without headaches. I bring deep experience in ChatGPT, AI Chatbot Development, AI Model Development, AI Development, and my sole focus is delivering a solution that gets you actual results. Here is what working together looks like: Zero Guesswork: We clarify the exact specs upfront so the execution is seamless. Flawless Quality: Built, tested, and vetted across mobile and desktop before it ever reaches your hands. If you want this taken off your plate today, send over any extra project details or files and I will start immediately. Best regards, Tarim

@aribaumer

Hello! I can help set up a local LLM AI model capable of handling complex tasks with a ChatGPT Astra style conversational experience. I can work on model selection, local deployment, inference optimization and integrating the required tools or APIs while keeping the setup practical for your available hardware. Recently,I have worked on AI applications involving LLM integration, computer vision and structured AI decision making. I can build a clean local setup and tune it for performance, response quality, and privacy. Best, Ariba

@huonghy89

Hi, I hope you are doing well. Very happy to bid your project because my skills are fitted in your project. I have strong experience with local LLMs, Python, PyTorch, Transformers, RAG, agentic workflows, prompt engineering, quantization, GPU inference, and production AI systems. I can build fully local AI solutions capable of complex reasoning, document analysis, coding, tool usage, structured outputs, and multi-step tasks without depending on external AI APIs. I have worked on similar projects using open-weight LLMs with local inference engines, vector databases, embeddings, RAG pipelines, memory, tool calling, and multi-agent workflows. I have also optimized models through quantization, GPU acceleration, context management, caching, and model routing to achieve strong performance on workstation-class hardware. I will evaluate your target tasks and hardware, select the most suitable local model and inference architecture, and build a private ChatGPT-style system optimized for reasoning quality, speed, memory usage, and future expansion. If you send the message, we can discuss the project more. Thanks.

@kafupeople

Hi For a local ChatGPT/Astra-style system, I’d first match the model to your actual hardware and the complex tasks you need it to handle rather than choosing a large model that runs too slowly or does not fit in memory. I can set up a suitable open-source LLM locally, configure inference, expose it through a simple chat/API layer, and test it against your real prompts for reasoning, language, statistics, or other workflows you need. I’ll also make the setup reproducible so you can run the model locally without depending on an external AI API. The main thing I need before choosing the model is your machine specification—especially GPU model/VRAM and system RAM. Thanks, Belal

@anas389

Hi, I can help you evaluate and set up a local LLM solution capable of handling complex tasks with a ChatGPT-like experience, while keeping inference and data processing on your own system. I can work with local models such as Llama, Qwen or Mistral, depending on your hardware and required capabilities. I can help with: • Selecting the right model based on your PC/GPU resources • Local deployment using Ollama or a similar runtime • Chat interface and conversation history • System prompts and task-specific configuration • RAG/knowledge-base integration if required • Tool/function calling for complex workflows • Performance and memory optimization • Testing reasoning, coding and general task performance • Documentation for running and updating the model locally I’ll first review your hardware and the exact tasks you expect the model to handle, then recommend the most suitable model rather than forcing a large model that your system cannot run efficiently. I’m available to start immediately. The budget and payment terms can be discussed and mutually finalized after reviewing the complete requirements and scope of work. Best regards, Anas

@shammij2

Hi Your project for an AI-powered video management and search system sounds ambitious and exciting. The main technical challenge is building an intelligent indexing pipeline that can efficiently scan, index, and understand thousands of video files. To achieve this, I'd employ a combination of OCR, AI analysis, and audio-to-text transcription to extract and manage metadata. In my experience as an AI developer, I've built complex search systems and AI applications using technologies like Large Language Models and AI chatbots. For instance, I recently developed a video indexing tool using Python and FastAPI that effectively categorized and made searchable a vast library of multimedia content, leading to significant improvements in data retrieval times. I commend you for envisioning a comprehensive system instead of a simple file organization. This approach will undoubtedly enhance your video library's utility. I can certainly help bring this vision to life and would love to walk you through the method and specific technologies I would apply to this task. Thanks, Shammi

@jtolbert0175

Hi You're looking for a local LLM AI model similar to ChatGPT Astra to handle complex tasks. The key challenge here is developing a custom LLM that captures nuances in different languages while maintaining performance and accuracy. Using the R Programming Language, I can leverage libraries like kerasR and tensorflow to train the model effectively, focusing on translation and multilingual capabilities, especially for German. My experience includes building AI-powered applications where I implemented language models to solve intricate tasks, resulting in tangible solutions for clients requiring seamless multilingual interaction. I appreciate your focus on a local model which is crucial for data privacy and localization. I can deliver a tailored solution and I'm ready to discuss further how we can create a high-performance LLM suited for your needs. Thanks, Jonathan