Local Large Language Models

Deploy and run powerful language models on your own infrastructure for enhanced privacy, security, and control over your AI applications.

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What are Local LLMs?

Local Large Language Models (LLMs) are powerful AI models that run on your own hardware or private cloud infrastructure, giving you complete control over your data and AI operations without relying on third-party APIs.

Local LLM Architecture

Figure 1: Local LLM Deployment Architecture

Benefits of Local LLMs

Enhanced Privacy

Keep sensitive data within your infrastructure, reducing the risk of data breaches and ensuring compliance with data protection regulations.

Improved Performance

Eliminate network latency by running models locally, resulting in faster response times and better user experience.

Full Control

Customize and fine-tune models to your specific needs without being constrained by third-party limitations or API changes.

Cost-Effective

Reduce operational costs by eliminating per-API-call pricing, especially for high-volume applications.

Offline Capabilities

Operate your AI applications without requiring an internet connection, ideal for secure or remote environments.

Custom Integration

Seamlessly integrate with your existing systems and workflows for a unified technology stack.

Available Local LLM Models

We support open-source models that can be deployed locally. (Following list only a snapshort - new models are added frequently)

LLaMA 3

Meta's latest open-source LLM with improved reasoning and coding capabilities.

Parameters: 8B, 70B
Context: 8K tokens
License: Custom (commercial use)
Specialty: General purpose, coding

Mistral 8x7B

Mixture of Experts model that delivers high performance with lower computational cost.

Parameters: 46.7B (8x7B active)
Context: 32K tokens
License: Apache 2.0
Specialty: Efficiency, reasoning

Falcon 180B

One of the largest open-source models with 180B parameters.

Parameters: 180B
Context: 2K tokens
License: TII Falcon License
Specialty: Complex reasoning

Ollama

Run and manage large language models locally with a simple API and model library.

Key Features: Local model management, optimized inference, easy API
Supported Models: LLaMA, Mistral, CodeLlama, and more
Platforms: Windows, macOS, Linux
Use Case: Local development and testing of LLMs

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LM Studio

User-friendly desktop application to run LLMs locally with a simple interface.

Key Features: No-code interface, model downloads, chat UI
Supported Models: GGUF format (LLaMA, Mistral, etc.)
Platforms: Windows, macOS
Use Case: Non-technical users, quick experimentation

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Implementation & Deployment

Deploying local LLMs has never been easier with modern tools and frameworks. Here are the recommended approaches:

Using Ollama


              # Install Ollama

              curl -fsSL https://ollama.ai/install.sh | sh


              
              # Run a model

              ollama run mistral

Python Integration


              # Using llama-cpp-python

              from llama_cpp import Llama

              llm = Llama(model_path="models/mistral-7b-instruct-v0.1.Q4_K_M.gguf")

              output = llm("Explain quantum computing in simple terms")

              print(output['choices'][0]['text'])

Deploying local LLMs requires careful consideration of hardware requirements, model optimization, and integration with your existing systems. Our team can help you with:

Hardware Assessment - Evaluate your current infrastructure and recommend the right hardware configuration
Model Selection - Choose the right model architecture and size for your specific use case
Optimization - Quantize and optimize models for efficient inference on your hardware
Deployment - Containerize and deploy models with proper scaling and monitoring
Integration - Connect with your existing applications and workflows

Hardware Requirements

Model Size	VRAM Required	CPU Cores	RAM
7B Parameters	12GB+	8+	16GB+
13B Parameters	24GB+	12+	32GB+
30B+ Parameters	48GB+	16+	64GB+

* Requirements may vary based on optimization techniques and quantization methods used.

Ready to Deploy Local LLMs?

Our experts can help you implement and optimize local LLM solutions tailored to your specific needs.